Passive imaging correction method using feedback

ABSTRACT

A method for image processing comprising providing an opening for entrance of light; the light being capable of being formed into an image; providing at least one optical element in an optical train configured to focus light; providing a variable aperture operatively associated with the at least one optical element; the variable aperture being placed in the optical train at an image plane and comprising mask settings for shielding portions of the light; providing an imager; providing at least one processor operatively connected to the variable aperture and imager; the at least one processor configured to control the passage of the light through the variable aperture; selectively masking portions of light using the mask settings of the variable aperture; obtaining image results using the settings; comparing image results obtained by the mask settings, and determining the phase correction that provides the optimal image results.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a divisional application of and claims priority toU.S. patent application Ser. No. 13/667,048, entitled “Passive ImagingCorrection System Using Feedback and Method Thereof,” by David H.Tofsted and Dr. Sean G. O'Brien, filed Nov. 2, 2012, herein incorporatedby reference in its entirety.

STATEMENT OF GOVERNMENT INTEREST

The embodiments herein may be manufactured, used, and/or licensed by orfor the United States Government without the payment of royaltiesthereon.

BACKGROUND OF THE INVENTION

The present invention is directed to, inter alia, passive correction ofturbulence affected incoherent imaging using an optical system (andmethodology) for, inter alia, reducing the effects of short-exposureblur due to atmospheric optical turbulence.

Optical signals passing through a time varying inhomogeneous medium,such as the Earth's lower atmosphere, can become significantly distortedwhen propagating over ranges of even as short as several hundred meters.The primary mechanism of this distortion is due to temperaturefluctuations driven by heating and cooling of the air which is mostsevere at the Earth's surface. In such cases, several optical distortioneffects impact propagating optical waves and signals. Coherentpropagation is significantly affected by turbulent scintillation(amplitude fluctuation) effects, and beam wander of propagating laserbeams. For incoherent wave sources being viewed by passive imagingsystems, three effects occur: Short exposure images show blurring ofpoint sources in the object plane. Point objects also appear to wanderin position due to angle-of-arrival variations. Thirdly, point sourcesseparated by angular distances exceeding a characteristic value (theisoplanatic angle) appear to wander independently.

Systems for correcting for turbulence effects on imaging through use ofan imaging system containing a Spatial Light Modulator (SLM) to modifythe phase of the incoming radiation have been disclosed, such as, forexample, M. A. Vorontsov, G. W. Carhart, and J. C. Ricklin, “Adaptivephase-distortion correction based on parallel gradient descentoptimization,” Opt. Lett. 22, 907-909 (1997) (hereby incorporated byreference) and G. W. Carhart, J. C. Ricklin, V. P. Sivokon, and M. A.Vorontsov, “Parallel perturbation gradient descent algorithm foradaptive wavefront correction,” in Adaptive Optics and Applications, R.Tyson and R. Fugate, eds., Proc. SPIE 3126, 221-227 (1997) (herebyincorporated by reference). These methods described in these papersfocus on two aspects: the use of a Spatial Light Modulator (ordeformable mirror, which functions in a similar fashion) and use of theParallel Gradient Descent (PGD) optimization method, which has nowevolved to be known as the Stochastic Parallel Gradient Descent (SPGD)method.

Ground-to-ground imaging-through-turbulence problems essentially involveimage blur, which is caused primarily by turbulence close to the systemreceiving aperture, and image distortion, which is due to turbulenceweighted toward the target object that is under observation by thesystem. Because the atmospheric optical turbulence strength is greatestclose to the ground, the dominant effect impacting ground-based imagingsystems is turbulence-induced blur close to the system aperture. As usedherein, the terminology “blur” signifies to make indistinct and hazy inoutline or appearance, reducing high angular-frequency detail, asopposed to obscuration which affects contrast, which reduces allangular-frequency detail equally. As used herein, the terminology“distort” as it relates to optics means a change in the shape of animage resulting from variations in the perceived relative angularpositions of different scene features of a given viewed object.

To correct for image blur, various system configurations have beenproposed in past work. These usually involve active systemimplementations that feature some sort of illumination device to producewhat is commonly known as a “guide star.” A guide star is a compactillumination source of known geometry and phase that can be imagedthrough the turbulent atmosphere by the imaging system. The system thenanalyzes the propagated characteristics of this guide star and uses theresults of this diagnosis to formulate a correction to the opticalsystem. This correction always involves a deformable optical device,either a deformable mirror or a spatial light modulator (SLM). The guidestar can be formed by an illumination beam propagated by the systemitself, producing an illuminated spot in the object field of view, or byan illumination source placed in the imaged object field of view andoriented toward the receiver optics. The following patent materials relyon the use of guide stars and/or the use of a wave front sensor: U.S.Published Application No. 2004/0208595, Free Space Communication Systemwith Common Optics and Fast, Adaptive Tracking, by Fai Mok and JamesKent Wallace; U.S. Published Application No 2005/0045801, State SpaceWavefront Reconstructor for an Adaptive Optics Control, by Carey A.Smith; U.S. Published Application No 2006/0049331, Adaptive OpticsControl System, by Carey A. Smith; U.S. Pat. No. 7,038,791,Signal-to-Noise Ratio Tuned Adaptive Optics Control System, by Carey A.Smith; U.S. Published Application No 2010/0080453 A1, System forRecovery of Degraded Images, by Nicholas George; and U.S. Pat. No.6,163,381, Dual Sensor Atmospheric Correction System, by Donald W.Davies, Mark Slater, and Richard A. Hutchin.

Unfortunately, there are several problems with the use of guide stars.First, a guide star approach is not a passive solution. Active systemsthat require the illumination of a target scene prior to detection ofsignificant targets are not stealthy and are undesirable in mosttactical situations that are of interest in a military situation.Second, many imaged objects may not have useful reflective propertiesthat will work properly with an illumination beacon. To provide a properguide star an object would need to have a corner reflecting or shallowconvex specular surface (a “glint” target) nearby. Most natural objectsare diffuse reflectors and thus do not return glints. Many man-madeobjects are also diffuse reflectors or have specular surfaces that aresharply curved and thus only return a very weak glint. Otheralternatives, such as placing an illuminator in the object plane,requiring objects of interest to mount glint reflectors, or forminglaser-induced fluorescence (LIF) guide stars on target surfaces areobviously not practical from an Army application standpoint. Anotherdifficulty with the guide star approach is that the coherent propagatingwave from a guide star is affected by turbulent scintillation, which ismost strongly weighted at the center of the optical path, not at thesystem receiver. Thus the guide star method is not optimized to producea useful result for removing turbulent blur.

Therefore, a means is needed to image objects through turbulent blurthat does not require an active illumination beacon (a guide star) andis optimized to sense turbulent blur perturbations on imaged incoherentradiation.

As opposed to active wave front sensing techniques, U.S. PublishedApplication No 2005/0151961, Surface Layer Atmospheric TurbulenceDifferential Image Motion Measurement, by John T. McGraw, Peter C.Zimmer, and Mark R. Ackermann simply attempts to sense the imagedistorting effects of the atmosphere without actually attempting tomodify or correct for turbulence effects.

Two known exceptions to the general approach of active wave frontsensing are Patent 2010/0053411 A1, Control of Adaptive Optics based onPost-Processing Metrics, by M. Dirk Robinson and David G. Stork, and themethod proposed in G. W. Carhart, J. C. Ricklin, V. P. Sivokon, and M.A. Vorontsov, “Parallel perturbation gradient descent algorithm foradaptive wavefront correction,” in Adaptive Optics and Applications, R.Tyson and R. Fugate, eds., Proc. SPIE 3126, 221-227 (1997). Both ofthese propose a system or a method to perform wavefront correction basedon post-processing of received imagery to produce a metric that is thenused in guiding the correction of images. The former proposed a system.The latter proposed a processing approach based on an algorithm. Bothbased their corrections on image analysis alone.

As indicated above, the guide star concept is generally not preferred inground-to-ground imaging applications for blur correction. In assessingthe impact of turbulence on boundary layer imaging, two observations aremanifest. First, the turbulence that is causing the most image blur isclose to the sensing aperture. Second, scene elements that are separatedin the scene by a significant angular separation experienceanisoplanatic effects limiting the ability of a system to correctturbulent image perturbations at large angular separation from the guidestar. Anisoplanatism means that turbulent perturbations in differentparts of the atmospheric field are causing different turbulentperturbations in different parts of an imaged scene. This effect impairsthe performance of guide-star-based systems, because turbulentperturbations on the guide star wavefront in one part of the image frameare not the same turbulent perturbations that impact scene elements inanother part of the image frame. Guide-star-based systems thus do not dowell at correcting for turbulent blur in different parts of an imagedscene, underscoring the need for a passive method that can correct forturbulence sequentially in different parts of the image.

Unlike systems that rely on a coherent “guide star” signal to provide asufficient density of photons to feed a wavefront detection process,atmospheric boundary layer imagers typically observe light emerging froma plurality of decorrelated emission sources. In particular, sourcepoints present on surfaces that are rough on the order of a singlewavelength of the propagating radiation, will not produce a singlecoherent source even in a point source sense. In this instance a secondtype of solution to compensating for turbulence has been sought. Thissecond form of solution involves a purely passive approach, of varyingimplementations, generally involving one or more post-imaging processingprocedures for detected signals to remove the impacts of turbulence. Onesuch algorithmic approach entails dewarping of the imaged field, toremove image distortion, based on analysis of the temporally varyingapparent positions of objects. Another approach uses long-term averagingof images to essentially remove the angle-of-arrival variations followedby inverse filtering using a best-guess of the long-exposure atmosphericMTF. Various combinations of these two approaches can be constructed,including analysis of and segmentation of images to separately studyconstant regions of images and regions that are considered to betemporally evolving that may contain scene elements of interest. Many ofthese procedures fall under the category termed the “lucky pixel” or“lucky patch” method, initially proposed by D. L. Fried, “Probability ofgetting a lucky short-exposure image through turbulence,” J. Opt. Soc.Am., 68:1651-1658 (1978). However, whereas Fried's initial proposalsuggested capturing complete distortion free images, laterimplementations of this concept [e.g. Carhart, G. and M. Vorontsov, Opt.Lett. 23, 745-747 (1998) or Vorontsov, M., JOSA A 16, 1623-1637 (1999)]first segment the images into a series of sections, analyze each sectionseparately to determine the relative clarity (spatial frequency contentbased on an image quality metric) of each, and then, on asection-by-section basis, proceed to composite a completereduced-turbulence equivalent image as a mosaic. Unfortunately, for manyterrestrial (ground-to-ground) imaging scenarios the probability ofobtaining any portion of an image that is free of significant turbulencemay be so small as to provide a negligible chance of obtaining a set ofnull-turbulence patches sufficient to construct an unperturbed image.One means of rapidly evaluating the overall quality of either an imageportion or a complete imaged scene involves constructing a sum ofsquares of the normalized image scene pixels [N. Mahajan, J. Govignon,and R. J. Morgan, “Adaptive optics without wavefront sensors,” SPIEProc., 228, Active Optical Devices and Applications, 63-69 (1980)]. AsMahajan et al. explained, the variance of the image information isrelated to the area under the combined atmosphere plus system MTF. Usingthis metric, it is possible to gauge the level of spatial frequencyenergy in a scene. Also, while D. L. Fried, “Probability of getting alucky short-exposure image through turbulence,” J. Opt. Soc. Am.,68:1651-1658 (1978) focused on only the probability of detecting a luckyshort-exposure image of a scene, a later study by R. E. Hufnagel, “TheProbability of a Lucky Exposure,” Tech. Memo. REH-0155, The Perkin-ElmerCorp. (1989) (hereby incorporated by reference) considered how thiscapability is enhanced for signals that have been partially correctedthrough the removal of an increasing number of phase perturbationaberration modes. In particular, Hufnagel considered cases involving 0(short-exposure image only), 3 (2nd order aberrations), 7 (2nd and 3rdorder aberrations) and 12 (2nd through 4th order aberrations corrected)modes compensated. Hufnagel's study, interpreted for the lucky patchproblem, indicates that while the lucky patch method acting on ashort-exposure image series could provide significant improvement forcases where the ratio of the diameter of the optics to the coherenceradius (X=D/r0) is no more than three, by correcting 7 aberration modes,the lucky patch correction technique would be one million times morelikely to find a lucky patch at X=10. This implies that the lucky patchapproach could be extended to turbulence conditions ten times stronger(triple the range) of the baseline lucky patch method alone.

In U.S. Published Patent Application No. 2010/0053411, entitled “Controlof Adaptive Optics based on Post Processing Metrics,” by M. DirkRobinson and David G. Stork, a system is proposed that performswavefront correction, based on post-processing of received imagery toproduce a metric that is then used in guiding the correction of images.The system appears to only apply to static targets.

However, it would appear that if one attempts to correct imagery basedsolely on analysis of received imagery, the number of phase perturbationaberration modes (expressed in terms of Zernike expansion functions[e.g. V. N. Mahajan, “Zernike annular polynomials and opticalaberrations of systems with annular pupils,” Appl. Opt. 33:8125-8127(1994) or G.-M. Dai and V. N. Mahajan, “Zernike annular polynomials andatmospheric turbulence,” J. Opt. Soc. Am. A 24:139-155 (2007)] presentat the system aperture gives rise to a problem. That problem is alimitation on how frequently a given mode may be corrected given aspecific rate of image collection by the optical system, in combinationwith the strength of aberration due to a specific mode. To assess theeffective number of active perturbation modes present one must be ableto evaluate the statistical state of the wavefront present at the systemaperture. D. L. Fried, “Optical resolution through a randomlyinhomogeneous medium for very long and very short exposures,” J. Opt.Soc. Am. 56:1372-1379 (1966) suggested that an appropriate measure ofthe decorrelation in the phase front present in the system aperture isthe turbulent coherence diameter, designated r₀. This length is a widthmeasured in a plane transverse to the direction of wave propagation overwhich the wave phase coherence decays by a value of exp(−1). For manycommon long-range surveillance receiving systems imaging objects atseveral kilometers distance the wavefront will become decorrelatedwithin the diameter of the receiver aperture at even moderate opticalturbulence levels (characterized by the dimensionless ratio X=D/r₀,where D is the diameter of the system aperture). In the case where Xsignificantly exceeds unity, the wave will exhibit random phasefluctuations that can cause image blurring effects, even accounting forshort-exposure imaging [Tofsted, D. H, “Reanalysis of turbulence effectson short-exposure passive imaging,” Opt. Eng., 50:01 6001 (2011) (herebyincorporated by reference)]. To describe these decorrelations in thepropagating phase front, various orthonormal families of basis functionsmay be utilized [e.g. V. N Mahajan, “Zernike annular polynomials andoptical aberrations of systems with annular pupils,” Appl. Opt.33:8125-8127 (1994). Fried, “Statistics of a Geometric Representation ofWavefront Distortion,” J. Opt. Soc. Am. 55:1427-1431 (1965)]. As theratio X exceeds unity, the effective number of non-zero expansion modesneeded to describe the wave perturbation function increasesapproximately as X². Therefore, for any given degree of turbulentperturbation one must have a specific plan to enable phase corrections[see detailed discussions of FIGS. 5, 11, and 14 through 18] based on anorganized methodology.

A further example of prior art is the application of the stochasticparallel gradient descent technique in tracking the effects of turbulentfluctuations. This stochastic method attempts to adjust a sequence ofdeformable mirror pistons by performing random fluctuations of thecurrent choice of piston settings, and adaptively modifying the bestguess of the correction state based on the outcome of each stochasticperturbation. Weighting methods may be used to selectively focus thealgorithm on the correction of lower order modes. The limitation of thisapproach is the high number of image samples to be collected rapidlyenough (several thousand sample images per second) to track the evolvingstate of the various perturbation modes. This is because the method isrelatively inefficient, relying on a stochastic adjustment procedure.Because the maximum sampling rate of an image at an adequatesignal-to-noise ratio is limited by the amount of ambient lightavailable to produce the image and the system's light gatheringcapability, sufficiently high frame rates may not be possible withoutthe augmentation of the system by a high intensity light source in theimaged scene to provide the necessary illumination. This amenity may notbe available in military or in many other contexts.

SUMMARY OF THE INVENTION

The present invention is directed to an improved adaptive optics controlsystem utilizing adaptive aperture techniques with or without phasecompensation techniques. A preferred embodiment system comprises avariable aperture, such as for example a controllable mirror, placed inan image plane of the system aperture to perform adaptive apodization, awavefront corrector, and a feedback system based on analysis of imagequality to determine updated settings to apply to the apodization mirrorand deformable wavefront corrector. The wavefront corrector may comprisea surface controlled by a plurality of actuators, which may beprogrammed to approximate a sum of weighted Zernike modes selected toapproximate the conjugate of the current short-exposure blur deformationto the propagated phase perturbations in the system apodized aperture.Specific settings of the phase map may be governed by a calculationbased on a programmed sequence of sub-aperture measurements of phase toproduce an estimate of the current atmospheric perturbations affecting agiven sub-image frame region of the observed scene. Feedback responsemay be used to determine the evolution of the current atmospheric stateand to adapt the phase correction for different sub-frame regions of theimage field of view. The system variable aperture (or apodization) maybe separately tuned to reduce the effective number of Zernikeperturbation modes that must be tracked by the system. The annularsetting of the apodization pattern provides control of both the maximumangular frequency response of the apodized system aperture as well ascontrolling the number of Zernike perturbation modes necessary to drivethe wavefront corrector.

A preferred embodiment of the present invention is directed to anoptical signal modification system designed to remove and correct severeamplitude and phase distortions in propagated fields emitted from aplurality of incoherent object plane source points based on the combinedoperation of a digital micro-mirror device (DMD) with or without aspatial light modulator (SLM), and a processing subsystem using imageplane feedback to optimize the choice of SLM and DMD settings based onpassive inputs. In a preferred embodiment, a dynamic feedback system maybe based on an ordered search procedure designed to sense sub-frameimage shifts of observed objects through selected sub-aperture regionsin combination with modeling of the conjugate phase necessary to drivethe correction settings for a plurality of Zernike perturbation modesfrom 2nd to 4th order. Coupled to this rapid Zernike computation methodis a radial model sampling method for controlling the system apertureapodization function involving setting of an inner and outer edge of anannular entrance pupil apodization pattern. The primary perturbationsthis design is configured to address are short-exposure blur effectsrelated to the atmospherically degraded apparent imaging systemmodulation transfer function (MTF). A primary objective of a preferredembodiment of the present invention is to best approximate the conjugateof the atmospheric perturbations affecting image quality. To form acoordinated pair of correction signals applied simultaneously to the SLMand DMD elements of the optical correction system, a master sequencingprogram is designed to (1) assess feedbacks from sub-aperture sampleimage processing results, (2) assign current settings for the SLM andDMD subsystems, (3) select successive sub-frame image regions on whichto focus the correction algorithm, and (4) schedule sequences ofsub-frame sub-aperture image collections for analysis and full-framefull-apodized aperture image collections for output based on optimizedSLM and DMD computed settings.

In an alternative embodiment, the SLM is absent, and the DMD isprogrammed to only model a variable system aperture, with or without anannular shape. The resulting system will select an optimized effectivesystem aperture diameter based on the current state of turbulence, whichis determined by feedback based on image quality. In both embodiments,the image quality for computing the settings of the system apertureapodization is assessed using a sum of squares of image pixel values ofa contrast stretched image, which thereby reflects the current level ofcorrection of blur, quantifying the approach of thesystem-plus-atmospheric modulation transfer function (MTF) toward anoptimal setting.

Alternatively, when computing the sum of squares, the image data can bemultiplied by a regional weighting function that focuses on a particularportion of the image field. This method permits the apodization controlsystem to selectively enhance different specific portions of the imagethat may be at different ranges, experiencing different levels ofturbulence-induced blur, thereby permitting the system to either focuson a single area of interest or to progressively scan across the fullimage field and generate a series of image patches that may be stitchedtogether to produce a complete clear image.

The preferred method comprises an adaptive system based on a passiveanalysis of scene content and optimization of the same through theaugmentation of the basic optics of a receiver system (lenses, mirrors,and stops) through the introduction of three specific additionalelements. The first element is a digital micro-mirror device suitablyintegrated into the optical path and connected and interfaced to acomputer or microprocessor control unit. This element adapts the shapeof the wave front that is permitted to pass through the optical train tothe final lens and be focused onto the image plane. The second elementis a spatial light modulator suitably integrated into the optical pathand connected and interfaced to a computer or microprocessor controlunit. This element controls the phase of the light across the wavefront. The third element is a feedback control circuit designed to testthe current state of clarity of the images being produced by the currentsettings of the optical adjustments of the optical system, to adjustsettings on the adaptive optical DMD and SLM elements to obtainsub-aperture sub-frame image sequences, to perform pattern matching ofsub-aperture sub-frame images to determine relative angle-of-arrivaloffsets between different sub-aperture sub-frame images, to compute aconjugate phase model based on measured angle-of-arrival offsets, toapply this conjugate phase correction model to the SLM, to collectfull-frame full-apodized aperture images, to supply said full images toan image output channel, and to sequentially control and/or react touser-directed control to select new sub-frame regions of interest onwhich to focus the feedback control circuit processing. The overall goalis to reduce wave front perturbations through aperture apodizationremoval of perturbation modes and optimize the wave front conjugationthat mitigates the effects of diffraction and turbulent distortions onthe propagated object scene.

In an alternative embodiment, the SLM is absent, and the feedbackcontrol circuit is programmed only to optimize the variable systemaperture apodization setting for the DMD, with or without an annularshape. The resulting system will select an optimized effective systemaperture diameter based on the current state of turbulence, which isdetermined by feedback based on image quality for a selected sub-frameregion. In the embodiments with and without the SLM, the image qualitymay be assessed as a sum of squares of image pixel values of a contraststretched image, which thereby reflects the current level of correctionof blur, quantifying the approach of the system-plus-atmosphericmodulation transfer function toward an optimal setting. Alternatively,when using the sum of squares methodology, the sum of squares image datacan be multiplied by a regional weighting function that focuses on aparticular portion of the image field. This method permits the Zerniketracking system to selectively enhance different specific portions ofthe image, thereby permitting the system to either focus on a singlearea of interest or to progressively scan across the full image fieldand generate a series of image patches that may be stitched together toproduce a complete clear image.

The invention may be optionally designed as a surface-based imagingsystem for observing objects within the boundary layer and/or surfacelayer portions of the atmosphere. The preferred embodiments may beoperated in concert with post-image acquisition processing methods whichare capable of further enhancing the obtained imagery.

BRIEF DESCRIPTION OF THE DRAWINGS

The embodiments herein will be better understood from the followingdetailed description with reference to the drawings, in which:

FIG. 1 illustrates a sequence of images depicting increasing distortioneffects characterized by increasing turbulence strength C_(n) ²(measured in dimensions of m^(−2/3)).

FIG. 2 is a schematic illustration of a simplified optics system.

FIG. 3 is an illustration depicting graphically the concept that formost imaging applications featuring typical Q parameter values between 2and 6, the peak performance of the system is obtained when X isapproximately 3.

FIG. 4 is a schematic illustration of a commonly used model, the Zernikepolynomials, a set of orthonormal expansion functions, for describingperturbations over a circular aperture.

FIG. 5 is a graphical illustration based upon a publication in 1989 byR. Hufnagel illustrating the problem of acquiring “lucky” images, i.e.,images that were free of significant degrees of turbulence-induced blur,wherein the results are distinguished by the number of degrees of“freedom” or as reinterpreted in the graph “degrees of correction” (DoC)used in partially conjugating or correcting the imagery corrected;wherein Hufnagel's “zero DoC” corresponds to acquiring short-exposureimagery (i.e. no adaptive correction at all).

FIG. 6 is a schematic illustration of an adaptive optical configurationcomprising features not shown in FIG. 2; including, a secondary set oflenses 6 and 7 that are used to create a Fourier plane parallel regionbetween them such that a wavefront of light travelling between lenses 6and 7 can have its phase manipulated by a Spatial Light Modulator 8 orother similar phase perturbation means such as a deformable mirror.

FIG. 7A is a schematic illustration of an optical configurationincorporating the principles of the present invention comprising aDigital Micro-mirror Device (DMD) 21 that has been located in the imageplane of the system entrance pupil with a corresponding focus point inthe DMD 21.

FIG. 7B is a schematic illustration of a preferred embodiment depictingthe functional capabilities of a preferred embodiment as the adjustableapodization effectuated by the DMD 21 permits reduction in the number ofperturbation “modes” to be corrected, making the correction ofturbulence procedure easier, improving sensor performance in thepresence of optical turbulence. The mode removal method is shownschematically (for the purposes of an example) as removal of centralportion 14 from aperture or pupil 10.

FIG. 8 is a schematic illustration wherein the positive lenses 3 in FIG.7A is expanded as a Cassegrain system telescope (31, 32, 33, 34).

FIG. 9 is a schematic representation of a preferred embodiment opticalsystem required to image entrance pupil 31 at the DMD 21 plane based onthe system fixed lenses (primary reflecting mirror 32 and secondarymirror 33 (reflections having been unfolded)) by the positioning andfocusing powers of positive lenses 22 and 6.

FIG. 10 is a schematic block diagram of a preferred embodiment system.

FIG. 11 schematically illustrates the impact of applying a givenaperture mask to a perturbation pattern in the form of an AnnularApodization.

FIG. 12 schematically illustrates plots of the Modulation TransferFunction of an imaging system for a central obscuration of relativediameter c=D1/D2 (where D1 43 and D2 45 are the inner and outerdiameters in FIG. 11A, respectively).

FIG. 13 is a schematic illustration of an object plane 1 “scene.”

FIG. 14 schematically illustrates a series of 8 radial spokes located atangles 22.5, 67.5, 112.5, 157.5, 202.5, 247.5, 292.5, and 337.5 degreesfrom the origin at the top of the circle; these radial lines denote theboundaries of 8 sampled regions subdividing the annular aperture intosub-apertures for the purposes of constructing the estimated phasemodel.

FIG. 15 schematically illustrates two examples of subdivision of anannular region into eight circular sub-aperture sampling regions for twodifferent ratios of c=D1/D2.

FIG. 16 schematically illustrates 8 sub-aperture masks with highlightshowing the relative position of the windowed region (in white) ascompared to the original aperture extent bounded by the black regions)and for each sub-aperture selected, a sub-frame image is taken(correlating to the Region of Interest in FIG. 13); each sub-apertureimage being taken through a different portion of the overall aperture;whereupon the apparent location of the main feature of interest in thesub-frame will tend to be shifted slightly from image to image due todifferences in the wavefront tilt experienced by light arriving from theobject field in different portions of the system aperture, and thisshifting in position can be tracked by using matched filteringtechniques (including pattern matching) to produce a vector 53 in eachsub-aperture image 51 to the centroid of the main object of interest 52.

FIG. 17 schematically illustrates the conversion of an angular shift ofA′ (the measured shifts given in pixels of shift times angular extentper single pixel) into phase form.

FIG. 18 illustrates the “means” to be used to splice together a sequenceof sub-aperture measured tilt values computed in the azimuthaldirection, forming an azimuthal phase perturbation function that isperiodic over 2π in the θ variable illustrated in FIG. 14.

FIGS. 19A through 19F are schematic representations of the basic modelsfor window masks.

FIG. 19A is a schematic illustration showing a type of annular mask thatmay be used with reflector telescopes with radial vectors [56] and [58]denoting the inner and outer radii of a masked annular region.

FIG. 19B is a schematic illustration showing a type of annular mask thatmay be used with reflector telescopes with radial vectors [56] and [58]denoting the inner and outer radii of a masked annular region.

FIG. 19C is a schematic illustration showing a type of annular mask thatmay be used with reflector telescopes with radial vector 58 denoting theouter radius of a masked annular region.

FIG. 19D is a schematic illustration showing a type of mask that may beused with reflector telescopes and illustrates a reduced circularaperture necessary for the sub-aperture images; wherein [61] is anoffset vector from the center of the aperture to the center of themask's open circular region, [62] denotes the radius of the open maskregion, and [63] denotes the boundary of the open region through whichlight may pass.

FIG. 19E is a schematic illustration providing the same functionalityfor a refractor telescopic aperture that has no secondary mirror centralobscuration (whose extent is denoted by circle [55] in FIGS. 19A-D),wherein the center of the mask's open circular region [62] denotes theradius of the open mask region, and [63] denotes the boundary of theopen region through which light may pass.

FIG. 19F is a schematic illustration providing the same functionalityfor a refractor telescopic aperture that has no secondary mirror centralobscuration (whose extent is denoted by circle [55] in FIGS. 19A-D), andillustrating a reduced circular apertures for the sub-aperture imageswith radial vectors [56] and [58] denoting the inner and outer radii ofa masked annular region.

FIG. 20 is a schematic illustration of masks that may be used prior tothe main sub-aperture testing phase (optionally some 50 to 100 masks intotal (the dots indicate intermediate forms of the basic mask)) thatcould be used to sense the level of the turbulence and to determine theoptimum annular aperture mask to be used in image correction.

FIG. 21 is a schematic illustration showing the most basic annularaperture mask set that could be used as the default obscuration approachin which a variable amount of the center of the system aperture isblocked in producing a variable annulus width; for example, there wouldbe some 20 of these masks pre-computed and loaded in memory on the DMDdevice.

FIG. 22 is a schematic illustration showing an alternative to the setshown in FIG. 21; where instead of masking off a variable portion of thecenter of the aperture, but keeping the maximum outer radius, ifturbulence conditions are strong enough, it may be necessary to insteadmask off the outer edge of the aperture by a variable amount (using some20 of these main masks loaded on the DMD).

FIG. 23 is a schematic illustration of a mask set comprising a series ofsub-aperture models that would be associated with the main annular maskset shown in FIG. 21, where for each main mask of the FIG. 21 mask set,there need to be 8 masks of the FIG. 23 type to provide sub-aperturesampling.

FIG. 24 is a schematic illustration showing a mask set comprising aseries of sub-aperture models that would be associated with the mainannular mask set shown in FIG. 22 where for each main mask of the FIG.22 mask set, there need to be 8 masks of the FIG. 24 type to providesub-aperture sampling.

FIG. 25 is a schematic illustration showing a mask set that could beused as a further option under extreme turbulence conditions in case thecentral obscuration of the system was too large to permitcharacterization of the sub-apertures around it.

FIG. 26 is a schematic illustration depicting a typical annular maskselected from one of the annular mask sets (from FIG. 21, 22, or 25)given a current turbulence state illustrated by the present coherencediameter r₀ whose length is illustrated by the accompanying arrow, andwhere δ=(D2−D1)/2. The main limitation in the choice of the mask thatmay be used is that π(D1+D2)/2, the circumference around the meanradius, must be less than 16*δ. Otherwise, eight sub-aperture imageswill not adequately sample the azimuthal phase depicted in FIG. 18.

FIG. 27 illustrates the path weighted impacts of ground based turbulencefor slant path propagation and the four types of propagation impactsillustrated in FIG. 32, with short-exposure blur effects [75] seen asthe most significant impact.

FIG. 28, illustrates the weighted impact of turbulent spatialfrequencies of wavenumber κ normalized relative to the system diameterD; which in effect depicts an analysis of the focus and astigmatismterms and reveals that the most significant wavelength affecting focusand astigmatism is approximately 3 times the diameter.

FIG. 29 is a block text description of the digital micro-mirror device,spatial light modulator, and feedback control circuitry.

FIG. 30 is a schematic illustration of an embodiment to the presentinvention comprising a digital micro-mirror device, spatial lightmodulator, and feedback control circuitry,

FIG. 31 comprises four graphs which compare Z₂ ⁰ (90) with Z₄ ⁰ (91)(Graph A), compares Z₁ ¹ (92) with Z₃ ¹ (93) (Graph B), compares Z₂ ²(94) with Z₄ ² (95) (Graph C), and compares Z₃ ³ (96) with Z₄ ² (97)(Graph D); illustrating the point that although they appear to showdifferences in their central regions, in the region beyond approximately|p|>0.8 each function is approximately linear.

FIG. 32 illustrates using Zernike polynomials (a set of orthonormalexpansion functions for a circular aperture) the impact of the centralobscuration on the complexity of the tracking task that must beaccomplished by the proposed invention.

FIG. 33 illustrates the basic path weighting effects of variousturbulence impacts on propagation, including short-exposure blur (71),scintillation (72), anisoplanatism (73), and angle-of-arrival (74).

FIG. 34 is an illustration showing daytime turbulence height profile.

FIG. 35 illustrates a diagram of path position involving an abstractexample of a problem that involves a system with aperture (79) farsmaller than the imaged field (81) having a typical size of the aperture(10 cm), imaged object (50 cm), and range to object (80) of 2 km.

FIG. 36 is a schematic illustration of a preferred embodiment,substantially similar to FIG. 7A, thus retaining the same numberingsystem and definitions as described in that figure, but replacing theadaptive SLM 8 with a simple mirror 9 in the optical system.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

The embodiments herein and the various features and advantageous detailsthereof are explained more fully with reference to the non-limitingembodiments that are illustrated in the accompanying drawings anddetailed in the following description. Descriptions of well-knowncomponents and processing techniques are omitted so as to notunnecessarily obscure the embodiments herein. The examples used hereinare intended merely to facilitate an understanding of ways in which theembodiments herein may be practiced and to further enable those of skillin the art to practice the embodiments herein. Accordingly, the examplesshould not be construed as limiting the scope of the embodiments herein.

The methodology of a preferred embodiment does not utilize anyrandomized search procedure, nor does it utilize any form of specializedemitting source in the object plane. Rather, a systematic searchtechnique is proposed, in combination with an adaptive aperture controlsystem, permitting the collecting of a sequence of sub-aperture images,constituting a sequence of circular mask images, evenly arranged overthe region of the main annular mask (of a type illustrated in FIGS. 20and 21) to be used for collecting full-frame images (typical setsconsist of four (4), six (6), or eight (8) sub-aperture masks), to besequentially applied by the DMD to collect information regarding thecurrent phase perturbation state around the currently selected annularmask, from which a complete phase correction solution can be computed.This optimized approach permits tracking fewer perturbation modes in thecontrolled (adapted) apodized aperture at higher levels of turbulencethan would be required for an un-apodized aperture or a randomizedsearch procedure. A preferred methodology both simplifies the overallproblem (by restricting the number of active turbulent modes in theadapted aperture) and can be handled more efficiently through use of asampling method using a sequential series of sub-aperture sub-framesample images. The rationale for this assessment is that method of thepresent invention both simplifies the overall problem (by restrictingthe number of active turbulent modes in the adapted aperture) and can behandled more efficiently through analysis of the series of sequentialsub-aperture images. This optimized approach permits tracking fewerperturbation modes at higher levels of turbulence than are sustainableusing a full aperture conjugation approach. The addition of, inter alia,the Digital Micromirror Device forms a critical new element thatfundamentally changes the approach to producing the correction forturbulence induced image distortion. The Digital Micromirror Devicefacilitates the optimized use of a Spatial Light Modulator, making thesolution simpler to evaluate and the conjugate correction easier togenerate. That is, any imaging system must balance the rate ofacquisition of full frames of image data against the noise produced at agiven light level and the image sample dwell time. A given order ofturbulence for a given aperture size and shape will require at least onedata sample per perturbation term in the aperture. The available lightlevel and the aperture settings determine the ability to correct for agiven level of turbulence. The ability to reduce the number ofturbulence perturbation modes and to efficiently correct for those modesprovide the rationale for the preferred embodiments, optimized to lightlevels for viewing naturally illuminated objects.

FIG. 1 illustrates image distortion simulations depicting the influenceof increasing turbulence strength measured by C_(n) ², the refractiveindex structure parameter. The effect of turbulence is estimatedrelative to the coherence diameter, r₀=3.018(k²LC_(n) ²)^(−3/5) forconstant C_(n) ² along the optical path, where k=2π/λ is the radiationwavenumber, λ is the radiation wavelength set to 1.5 μm, L is theoptical path length of 7.5 km. A preferred embodiment of the presentinvention may provide the capability to adaptively correct for turbulentphase perturbation up to a D-to-r₀ ratio of 10, where D is the maximumdiameter of the system.

FIG. 2 illustrates a very simple imaging system comprising an objectplane 1, an image plane 4, and a single positive intervening lens 3. Ifthe optical turbulence 5 is not present, the photons 2 would effectivelyfollow straight paths from the object plane 1 to the system lens 3 wheretheir paths are deflected in such a manner that the expanding sphericalwave emitted from every point in the object plane is imaged onto acorresponding conjugate image point on image plane 4. This is, ofcourse, a simplified view, and the image of a point source would bediffraction limited by the diameter of the system aperture correspondingin this case to the diameter of lens 3.

When optical turbulence (denoted as block 5) is present along theoptical path between the object plane and the receiving aperture, thepresence of refractive turbulence (turbulent temperature fluctuations inthe atmosphere induce changes in the refractive index of the air) (shownas block 5) create random small tilts in the propagating direction ofphotons travelling through the air between the object plane 1 and thesystem aperture 3. These tilts cause different photons arriving atdifferent portions of the system aperture to be focused onto differentpoints of the image plane 4, creating a blurred image spot that may alsobe displaced from its original image point.

Another way of picturing the image distortion effects of the turbulenceis by considering the phase perturbations imposed by the atmosphere dueto propagation of light from a single image point. In FIG. 7B, bottomleft, phase perturbations (e.g., 12) are shown pictorially as light anddark patches varying across the system entrance pupil or aperture 10.The complete aperture has an entrance pupil diameter D (11). Typicalphase perturbations, illustrated as a series of patches of type 12 areconsidered to have a characteristic width 13 termed the turbulent“coherence diameter” (r-naught or r₀). It is common practice tocharacterize the turbulence impact on a system with aperture diameter Dusing the ratio X=D/r₀. R-naught is formally defined as the distanceover which the propagating wavefront from a point source decorrelates bya factor of exp(−1). Of particular interest is the performance of asystem with no turbulence correction. If no turbulence were present, alarger diameter aperture will always resolve greater image detailaccording to the value of the ratio Ω₀=D/λ, which determines the maximumangular frequency resolvable by the system. When turbulence is present,though Ω₀ is unchanged, the system's ability to image is degraded suchthat for X=D/r₀>3 the system performance actually decreases due toturbulent blur effects when D is increased. This behavior is computedbased on the “Resolution,” the integrated volume under the system'sModulation Transfer Function (MTF) for either short-exposure (snap-shot)or long-exposure (astronomical long-exposure imaging) cases in FIG. 3.The Response functions are plotted for a standard circular aperturesystem for varying X parameter values for different imaging scenarioswhere Q=D/(λL)^(1/2) is a measure of the diffraction influence on thesystem.

As illustrated graphically in FIG. 3, the peak performance of a systemoccurs when X is approximately 3. For most imaging applications the Qparameter is between 2 and 6, meaning that for most systems diffractionvariations in performance are minimal when X>2.

To understand how the present invention can improve the capability forturbulent phase correction one first must introduce a model fordescribing perturbations in the system aperture. The most commonly usedmodel is that of Zernike polynomials, a set of orthonormal expansionfunctions for a circular aperture (FIG. 4).

FIG. 4 illustrates graphically the relations between Zernike polynomialsof various orders and azimuthal dependencies, and their connections tolens design. Each box 17 is designed to represent a particular Zernikepolynomial. These are a series of orthogonal functions designed torepresent arbitrary contiguous functions on a circular two-dimensionalplane, such as the entrance aperture of an optical system. Each Zernikefunction is designated by two indices: “n” (16) represents the maximumradial axis power (the “r” radial parameter in FIG. 11A), “f” (15)represents the azimuthal order. The Zernike polynomials along aparticular row of the table are thus used to represent a given order ofturbulent perturbations. In general, each Zernike polynomial consists ofa product of two functions, a radial function dependent only on “r”, andan azimuthal function dependent only on an azimuthal variable “a”, asindicated in FIG. 11A. The azimuthal dependencies are given as eithersine or cosine functions of different orders. For positive f indices theazimuthal dependence is cos(fa). For negative f indices the azimuthaldependence is sin(fa). The different rows (orders) of the diagram areoften referred to by names affiliated with lens vision corrections, suchas focus and astigmatism. Tip and tilt are of particular interest inatmospheric turbulence studies as these are associated withangle-of-arrival variations. However, as D. L. Fried, “Opticalresolution through a randomly inhomogeneous medium for very long andvery short exposures,” J. Opt. Soc. Am. 56:1372-1379 (1966) pointed out,tip and tilt do not (by themselves) degrade propagated image quality.They only cause the location of a given image to be shifted on the imageplane. Likewise, the piston effect only alters the overall mean phase ofthe wave entering the system, but does not alter the image quality.Note, also, that it is expected that the fixed system optics will removethe mean spherical wave focus aberration arising from the propagation,so that all that remains is to correct for various turbulence relatedperturbations.

With that in mind, any true corrections to remove turbulence blureffects will start with the n=2 row of the table. The term “Degrees ofCorrection”, or “DoC”, denotes the number of Zernike terms beingcorrected (“conjugated”). This term expresses the concept that theoptical system sets a phase adjustment to the SLM that is such that itexactly (within the degree capable for the SLM device used) removes agiven Zernike perturbation component. DoC=3 refers to removal of all n=2row Zernike elements. DoC=7 refers to removal of all n=2 and n=3elements. DoC=12 refers to removal of n=2 through n=4 elements. Lastly,DoC=0 refers to simply collecting short exposure imagery where no phaseconjugation has been applied to remove any perturbations.

These conjugation categories were used by R. Hufnagel (Hufnagel, R. E.,“The Probability of a Lucky Exposure,” Tech. Memo. REH-0155, ThePerkin-Elmer Corp. (1989)) to quantify the ability to avoid turbulentimage degradations when a given number of turbulent perturbation modeshad been corrected (conjugated). A portion of Hufnagel's main figure hasbeen re-digitized and re-formatted as FIG. 5. Hufnagel's paperconsidered the problem of acquiring “lucky” images, i.e. images thatwere substantially free of turbulence-induced blur. He distinguished theresults he obtained according to the number of degrees of “freedom,” or,as in the re-interpreted result plotted in FIG. 5, the number of“degrees of correction” (DoC), “partially conjugated” or corrected inthe imagery collected. Hufnagel's zero DoC line corresponds to acquiringshort-exposure imagery (i.e. no adaptive correction). Hufnagel'scalculations indicate a zero DoC system is ineffective beyond X=D/r₀=3,corresponding to the peak of the system response curve of FIG. 3. Forcases involving adaptive partial conjugation, Hufnagel's DoC=3, 7, and12 curves indicate significant improvement is possible even if only someof the active wavefront perturbation modes are corrected. Since thecoherence diameter, r₀, is proportional to range L to the −⅗th power,the DoC=3 curve illustrates that for the same degree of resolution asthe DoC=0 case, the system effective range is double the uncorrectedperformance (actually 1.752). Hufnagel's DoC=7 curve corresponds to atripled (actual 2.66) range capability, while the DoC=12 curvecorresponds to an approximately quadrupled (actual 3.72) rangecapability.

Therefore, a system that could correct for only 3, 7, or 12 Zerniketerms, could perform imaging tasks out to D/r₀ values of 5.5, 7.5, or9.5 versus the same performance of the DoC=0 case operating out toD/r₀<4, or a substantially increased range capability. The preferredembodiments described below detail the means of implementing andoperating such a system. However, for the sake of completeness it isnecessary to describe in some detail how such a system differs fromother previous wavefront correction systems.

Schematically, most major active systems can be considered to berepresented by an optics diagram of the type shown in FIG. 6. The FIG. 6system contains additional features designed to mitigate turbulenceeffects beyond the basic system shown in FIG. 2. In addition to theobject plane 1, turbulent atmosphere 5, perturbed propagating photons 2,main system entrance pupil and fixed lens system 3, and imaging plane 4,a secondary set of lenses 6 and 7 is used to create a Fourier planeparallel region between them. Light travelling between lens 6 and 7 canhave its phase manipulated by a Spatial Light Modulator 8 or othersimilar phase perturbation means such as, for example, a deformablemirror. Usage of a deformable mirror (or, alternatively a spatial lightmodulator) may involve various attempts to adjust a sequence ofdeformable mirror pistons by performing fluctuations of the currentchoice of piston settings (or alternatively SLM modulations), andadaptively modifying the best guess of the correction state based on theoutcome of each stochastic perturbation.

FIG. 7 illustrates the schematic of the optical system of the mainpreferred embodiment. Augmenting Spatial Light Modulator 8 takes asystematic, efficient, non-stochastic approach to wavefront modulation.Using the preferred method, it is possible to order the combinations ofsample conditions “tested” through a dynamic algorithm involving sampleimages collected with a specific set of sub-aperture masks associatedwith a given main annular mask model. Also, different perturbation modeswill evolve at different rates. It is expected, however, that the mostrapidly evolving modes may also carry the least impact on the overalldistortions in image quality in the image plane. On the other hand,those modes that have the most impact on image quality may be relativelyslowly evolving and therefore require less attention when deciding whichperturbation modes to track most closely. Hence, there will be anoptimal combination that focuses just the right amount of trackingresources on just the right modes that optimizes the system performance.The optimal combination cannot be determined until usage of anassemblage of a preferred embodiment.

In the optical train of FIG. 6, provided for the purposes of comparison,there may exist several reflecting mirrors (as symbolized by the planemirror 9) guiding the light through the final focusing lens 24 onto theimage plane. Not shown in this figure is a sensing system that usuallycomprises a wavefront sensor (WFS), typically a Shack-Hartmann device,or in some cases a Linear Shearing Interferometer, or sometimes both.Regardless of the method used to sense the wavefront, there is alwaysthe requirement that a coherent source must always exist in the objectplane (or near it) in order to provide the known radiation source thatcan be sensed by the WFS. Without such a known source, none of theseactive methods work. Often such embodiments require a laser source inthe vicinity of the scene to be sensed, leading to a severe limitationon the utility of such techniques/instruments.

Consider next the optical train that is provided by a preferredembodiment of the present invention, shown in FIG. 7A. In FIG. 7A aDigital-Micro-mirror Device (DMD) 21 has been located at an image planeof the system entrance pupil 3, such that a point in the entrance pupilwill have a corresponding focus point (denoted by focusing rays) in theDigital-Micro-mirror Device (DMD) 21. To facilitate this goal, a secondpositive lens 22 may be added between the system's main telescope(symbolized here as the single lens 3).

The location of the optical element 21 and the particular values of thefocal lengths of the lenses 6 and 22 are instrumental in the operationof the instrument depicted in FIG. 7A. FIG. 7A illustrates, in schematicor abstract fashion, a preferred embodiment adaptive optics controlsystem for removing the effects of short-exposure image blur ofincoherent imaged scenes. The object plane 1 to be viewed is seenthrough an evolving optically turbulent medium 5. Rays of light 2 passthrough the medium 5 and are randomly delayed as they enter the system'sentrance pupil 3. The system's telescopic or refractive lens opticaltrain is represented in this figure solely by lens 3. To prepare theincident radiation for the apodizing and phase modulating steps theincident radiation is passed through at least two shaping lenses (22 and6). These result in a wave that is propagating approximately as a planewave that is directed against a Digital Micro-mirror Device (DMD) (21).Though the FIG. 7A shows the passage through the DMD following straightlines, in actuality the beam would be reflected from 21 at a finiteangle. The plane wave would then be directed against a Spatial LightModulator (SLM) (8), further directed through the optical system via oneor more reflective surfaces (9), eventually reaching a focusing lens 7and directed to imaging plane.

The positioning of the DMD 21 is chosen such that the plane of (6)occurs at a real focal plane of the system entrance pupil (3), asdenoted by light ray lines 2.

FIG. 7B is a schematic illustration of a preferred embodiment depictingthe functional capabilities of a preferred embodiment. The adjustableapodization effectuated by the DMD 21 permits reduced number of modes tobe corrected to produce improved sensor performance in presence ofoptical turbulence. The reduced number of modes may be, for example, berepresented by the box ZR in FIG. 7B. Note that at the Z₁ level, thepiston has been deleted as unnecessary. Likewise, the tip and tilt level(shown in FIG. 4) has been deleted. Correction of turbulence is madeeasier after removing several perturbation “modes” (central portion 14removed from aperture or pupil 10).

FIG. 7B illustrates, diagrammatically, the impact apodization has inreducing the order of complexity of the random phase pattern of apropagated light wave in the system aperture. The full system entrancepupil is again designated by 10. The width of the aperture 11 isdesignated D, the system entrance pupil (aperture) diameter. Within thisaperture, the phase perturbations of a propagating point source areillustrated abstractly as patches 12 in which the propagating wave frontis approximately coherent. The characteristic width of these patches isassociated with the term “coherence diameter” (13) and is defined as alength in the transverse plane to the main axis of propagation overwhich the wave reduces in coherence to exp(−1) of its value at zerodistance. Coherence length is denoted as “r_(o)” (read r-nought). In theillustration, the number of independent coherence patches passed by theaperture is reduced from 15 to 9 when the center 14 of the aperture isblocked by the apodization technique. It is anticipated that a similarreduction will occur when modeling these phase patterns using a Zernikepolynomial expansion method.

In brief, the upper left portion of FIG. 7B schematically illustratesthe basic problem to be solved, where turbulent phase perturbations ofthe turbulent atmosphere 5 cause image distortions (blur andangle-of-arrival problems). The aperture 10 in the bottom left corner ofFIG. 7B schematically depicts or represents the shape and physicalextents of these perturbations. The lower right portion of FIG. 7B, is adiagrammatic attempt to show graphically the pattern of the Zernikepolynomials, but the representation of these functions is actually muchbetter in the color FIG. 4 of the plot. Each Zernike pattern is shownwhere color is used to show varying function value. Red is positive,blue is negative, and green is zero. As was pointed above, the Z₀ ⁰pattern, labeled piston, along with the tip and tilt terms, do notaffect image quality. They are labeled with an “X” in FIG. 7B becausethey do not need to be corrected since they do not impact blur.

Shown in the upper portion of FIG. 7B is a preferred embodiment imagecorrection optical system comprising an Adjustable Apodizer (AKA DMDoptical element) 21. Utilizing DMD 21, the center of the system apertureis variably obscured (the descriptions associated with FIGS. 11, 19A-F,26 illustrate this concept). Given that the center of the aperture canbe obscured, the benefits include those depicted in box ZR of FIG. 7B.Moreover, the aperture 10 in the lower leftmost aperture 10 depicts theunobstructed aperture whereas the aperture 10 having the central portion14 removed represents the obstructed aperture. Note that there are 15perturbation regions in the leftmost aperture 10, while in the centrallyobstructed aperture 10 to the right there are only 9 perturbationregions. Blocking part of the aperture removes perturbations. By sodoing, the problem of correcting for the turbulence becomes easier byremoving several perturbation “modes” that one no longer needs to track.

The schematic drawing in the lower right section of FIG. 7Bschematically illustrates this effect, as three of the Zernike terms areblocked out with the letter X. The central obscuration is depicted inboth the Z₂ ^(f) row and the Z₄ ^(f) row of the lower right section ofFIG. 7B. As represented by the arrows, with the central obscuration inplace the patterns Z₂ ⁻² and Z₄ ⁻², Z₂ ⁰ and Z₄ ⁰, and Z₂ ² and Z₄ ² arevirtually identical. That is, in representing the aperture it will notbe necessary to track all 6 of the identified terms, only 3, the other 3“map into” the same space as the upper three when the aperture issufficiently apodized. The arrow pointing from the apodized circleinside the rectangle ZR and the Zernike polynomial representations isdesigned to indicate that it is common that the phase is expanded interms of a weighted sum of Zernike terms and that under thecircumstances of an apodized aperture, fewer terms are needed torepresent the same phase pattern.

The upper right section of FIG. 7B correlates in part to FIG. 10 of thedisclosure. Arrows are used to depict the highlights of the phasemodulation and apodization control for performing the adaptive part of apreferred embodiment solution. FIG. 10, a system block diagram of apreferred embodiment, attempts to show how the control flow of theinvention would work, as opposed to FIG. 7B which depicts the generalconcept of a preferred embodiment optical system.

In FIG. 8, the positive lenses 3 and 22 of FIG. 7A are expanded as aCassegrain system telescope (31, 32, 33, 34) and a field lens 22. FIG.8. provides a more detailed picture of the functioning of a reflectortelescope embodiment of the system.

In FIG. 8, light arriving from the object plane 30 passes through thesystem entrance pupil 31 and is reflected from the telescope's mainmirror 32 (effectively a positive lens). The light then travels to thesecondary mirror 33 where it is again reflected and passes out throughthe back aperture stop of the telescope 34. The converging light willeventually reach some focal point (natural image plane), but before thiscan occur, an additional positive lens 22 is positioned in the opticalpath to cause the focal point to occur at a shorter range. This causesthe light rays emerging from the focal plane to diverge more strongly.Positive lens 22 must be placed prior to the focal point of the exitingrays in order to cause the rays to diverge more rapidly beyond focalpoint. The reason for requiring this extra lens to be present can beseen in FIG. 9.

FIG. 9 is a schematic representation of the optical system required toimage the entrance pupil at the DMD position 21 based on the systementrance pupil 31, the primary reflecting mirror at 32, and thesecondary mirror (reflections have been “unfolded”) at 33; i.e., theoptical paths of the telescope's two mirrors have been “straightenedout” (reflections eliminated) and are represented by effective lenses 32(primary mirror) and 33 (secondary mirror). The entrance pupil 31permits near-parallel light rays to enter the system. This light isconcentrated by lens 22 (equivalent to lens 22 in FIG. 8) and then, onceinverted, is passed through positive lens 6 to form an approximatelyparallel beam directed toward the DMD (21). Also traced through thesystem is a point at the center of the system entrance pupil 31 alongray lines 23 showing that the DMD 21 is in a focal plane of the systemaperture. The choice of two positive lenses 22 and 6 is necessary basedon the dual requirements that rays 2 be parallel upon exiting lens 6 andthat rays 23 must focus at 21. As can be seen, the two separate positivelenses (22 and 6) ensure that both light rays 23 traced from a point inthe entrance pupil 31 will focus at the DMD 21, and that parallel rays 2emerging from the entrance pupil 31 will pass through the plane of theDigital-Micro-mirror Device (DMD) 21 as parallel rays. The only means ofaccomplishing both tasks is by inverting the rays (between 22 and 6) andby using two positive lenses. Both 22 and 6 are positive lenses and iflens 22 is placed in the optical train before the first focal point ofthe main telescope. By choosing to place the DMD in the image plane ofthe system's entrance pupil, whatever apodization effects are applied bythe DMD are “effectively” also applied in the system entrance pupil(within the limits of diffraction and spread due to the use of finiteoptics and the current turbulence conditions).

This optical system supports the exploitation of the DMD (alsodesignated as Adaptive Aperture 21) in the preferred method of blurcorrection system schematically illustrated in FIG. 10, as constructedin accordance with the principles of the present invention.

The Optical System in the embodiment depicted in FIG. 10 comprises anoptical train, including the Telescope and Fixed Optics 101 describedpreviously, the adaptive aperture 102 (the DMD 21 and hardwareinterface), the adaptive phase (an SLM and hardware interface) 104, andan Image Capture 108 means. The Adaptive Aperture 102 comprises the DMD21 and its hardware interface and cabling. One source for DMD devices isTexas Instruments' Digital Micromirror Device (DMD). A DMD can beconnected to a PC class computer using Logic PD's DLP LightCommanderDevelopment Kit. The Texas Instruments DLP Kit permits interfacing tothe DMD through a PC whereby up to 1792 1-bit (black or white) XGAresolution (1024 by 768) images can be stored in the system memory.These images can be indexed to permit rapid control of the 1024-by-768resolution micro-mirror surface. The Series 450 DMD micro-mirror controlpermits selection of the reflected region, timing of the choice ofregion selected for reflection, and is user controllable.

As described in Wikipedia, a digital micromirror device, or DMD, is anoptical semiconductor that is the core of DLP projection technology andwas invented by Dr. Larry Hornbeck and Dr. William E. “Ed” Nelson ofTexas Instruments (TI) in 1987. The DMD project began as the DeformableMirror Device in 1977, using micromechanical, analog light modulators. ADMD chip has on its surface several hundred thousand microscopic mirrorsarranged in a rectangular array which correspond to the pixels in theimage to be displayed. The mirrors can be individually rotated ±10-12°,to an on or off state. In the on state, light from the incoming raybundle is reflected into the lens making the pixel appear bright on thescreen. In the off state, the light is directed elsewhere (usually ontoa heatsink), making the pixel appear dark. The mirrors are made out ofaluminum and are around 16 micrometers across. Each one is mounted on ayoke which in turn is connected to two support posts by complianttorsion hinges. In this type of hinge, the axle is fixed at both endsand literally twists in the middle. Further according to Wikipedia, twopairs of electrodes control the position of the mirror by electrostaticattraction. Each pair has one electrode on each side of the hinge, withone of the pairs positioned to act on the yoke and the other actingdirectly on the mirror. The majority of the time, equal bias charges areapplied to both sides simultaneously. Instead of flipping to a centralposition as one might expect, this actually holds the mirror in itscurrent position. This is because attraction force on the side themirror is already tilted towards is greater, since that side is closerto the electrodes. To move the mirrors, the required state is firstloaded into an SRAM cell located beneath each pixel, which is alsoconnected to the electrodes. Once all the SRAM cells have been loaded,the bias voltage is removed, allowing the charges from the SRAM cell toprevail, moving the mirror. When the bias is restored, the mirror isonce again held in position, and the next required movement can beloaded into the memory cell. The bias system is used because it reducesthe voltage levels required to address the pixels such that they can bedriven directly from the SRAM cell, and also because the bias voltagecan be removed at the same time for the whole chip, so every mirrormoves at the same instant.

As depicted in FIG. 29, in addition to the components of a basic opticssystem (e.g., lenses, mirrors and stops), three additional elements areused in conjunction with the preferred embodiments, which can be usedseparately or in combination with one another. The first element is adigital micro-mirror device (e.g., DMD 21) suitably interfaced andconnected to a computer or microprocessor control unit into the opticalpath. This element adapts the shape of the wave front that is permittedto pass through the optical train to the final lens and be focused ontothe image plane. The second element is a spatial light modulator (SLM 8or deformable mirrors) suitably interfaced to a computer ormicroprocessor control unit into the optical path. This element controlsthe phase of the light across the wave front. The third element is afeedback control circuit designed to test the current state of clarityof the images being produced by the current settings of the opticaladjustments of the first and second elements. Based on the latestobserved clarity, previously tested settings, and a controller algorithmconnected between the feedback circuit and the controlling algorithmsrunning the first and second elements, the computer invokes a series ofcorrective adjustments to the first two elements, seeking a best fit tooptimize the wave front conjugation that mitigates the effects ofdiffraction, propagation, and turbulent distortions.

The feedback system utilizes an analysis of image quality to determineupdated settings to apply to the apodization mirror (DMD 21) anddeformable wavefront corrector (e.g., spatial light modulator SLM 8 ordeformable mirrors). The wavefront corrector has a surface controlled bya plurality of actuators. These actuators are programmed to approximatea sum of weighted Zernike modes selected to approximate the conjugate ofthe current short-exposure blur deformation to the propagated phaseperturbations in the system aperture. Specific settings the phase mapare governed by a programmed sequence of perturbations designed toproduce a basic estimate of each of N Zernike modes over a series of N+1sample images. Feedback response is used to selectively modify the meansettings of the Zernike modes according to the current atmosphericstate, with modifications to the present setting based on response fromindividual image responses to new modified settings. The systemapodization (e.g., DMD 21) may be separately tuned to reduce theeffective number of Zernike modes that must be tracked by the system. Anannular setting on the apodization pattern permits the maximum angularfrequency response of the complete system aperture while simplifying themodeling of the Zernike perturbations used to drive the wavefrontcorrector (e.g., spatial light monitor SLM 8 or deformable mirror).

The Adaptive Phase component 104 in FIG. 10 may be referred to inconjunction with the terminology wavefront corrector and comprises aspatial light modulator (SLM 8) and associated interface hardware. Forexample, Thorlabs sells a kit for an SLM device which could be adaptedto provide a prototype device the enabling capability necessary for aproof-of-principle demonstration of the invention. This SLM is capableof 5 kHz operational variations which is greater than the 1-2 kHzenvisioned necessary to support ground-level correction of turbulence.

The Image Capture element 108 comprises an imaging camera and associatedframe grabber or other hardware interface and associated cabling. Anexample of the type of camera suitable for development purposes is theBasler Ace acA2000-340kc camera capable of 340 frames per second fullimage capture rate, but also up to several thousand frames per secondcapture for reduced (subframe) region of interest image captures. Inconjunction with this camera, the EPIX PIXCI-E8 Frame Grabber with dualcoaxial cables provides a data collection capability sufficient tocapture the image data produced by the Basler camera.

In addition to the optical system that has been the focus of thediscussion up to this point, a controller software package includingseveral sub-modules will be located on a PC type computer. Thesesub-modules interact through a main controlling software program termedthe Master Adaptive Controller 106. The sub-modules of this main controlsoftware could potentially be either contained on the same computer orbe subtasked to independent micro-controllers in communications with theSLM and DMD submodules. These two modules are the Aperture Controller103 and the Phase Controller 105. Each module can take simpleinformation produced by the Master Adaptive Controller 106 and translatethis information into specific control inputs required by each hardwaresub-module to set the hardware to its desired dynamic setting.

The Image Capture module 108 contains the camera and frame grabberequipment, but it also includes a small module to either (a) collect afull frame image and pass it out to be displayed to the user or (b)collect subframe region of interest images and pass these on to theImage Processing module that determines the image state metrics andpasses the results of this analysis to the Master Adaptive Controller.

The methods used in the processing of the data as well as the means ofmodifying the DMD in support of the phase correction solution are nextdescribed. Referring to the model of the phase variations present in asystem aperture as illustrated in the lower left corner of FIG. 7B, theperturbations in the phase had a certain characteristic length scalethat tended to shrink as turbulence worsened. Here, the impact ofapplying a given aperture mask to that perturbation pattern in the formof an Annular Apodization (FIG. 11) will be considered.

FIG. 11 illustrates the general DMD apodization and SLM phase controllerschemes. In a preferred embodiment, the master controller software willdirect information concerning the new settings to be applied to the DMDto produce an inner circle 43 and an outer circle 45. In terms of phase,a series of coefficients will be used to designate the phase along theinner circle 43, the middle circle 44, and the outer circle 45 using ascheme that permits either linear phase variations across the spanbetween the inner and outer circles or a quadratic model. In theazimuthal direction, denoted by angle “a”, a series of Fourier expansionterms will be used. The exact nature of this model is discussed furtherbelow.

An alternative choice to the selection of an annular apodization patternn annular apodization pattern might be to simply choose an apodizationpattern that restricts the aperture so only (on average) a single modeof turbulence is present (i.e. X=1). As shown in graphically in FIG. 7B(bottom left corner) such a choice is close to the diffraction limitedbehavior (that is, in the language of FIG. 7B, the short-exposureresolution, R_(S), approximately equals the diffraction limited behaviorof X²). But by choosing to stop the aperture down, the maximum frequencypassed by the system entrance pupil, given by Ω₀′=D′/λ, is significantlyreduced when the new entrance pupil diameter D′ may be considerablysmaller than the original system diameter D.

An annular apodization pattern has two advantages over an unobstructedcircular pattern. First, as comparison between FIG. 11 (right annulus B)and FIG. 7B (bottom left corner) reveals, by applying a central maskseveral independent phase perturbation regions will be removed from thecentral region of the entrance pupil (in the illustration, sixperturbation regions are masked off). This masking reduction simplifiesthe determination of the dynamic perturbation pattern for a given regionof the object plane. Secondly, regardless how large the centralobscuration is, the annular pupil system will always have the samemaximum angular resolution as an unobstructed system of the same outerdiameter. This is because the outer diameter always determines themaximum angular frequency response. This point is illustrated in FIG.12, which plots the MTF of an imaging system for a central obscurationof relative diameter c=D₁/D₂ (where D₁ and D₂ are the inner diameter 43and outer diameter 45 in FIG. 11 (part A).

Referring once again to a preferred embodiment system comprising an SLM8 (for phase correction) and a DMD 21, this system is more effectivethan a system featuring a Wavefront Sensing system, since such systemsare practically impossible to implement in the atmospheric boundarylayer because one can never guarantee the presence of a “guide-star” inthe object plane unless one places such a beacon there. In general, onemust simply use the available light arising from natural scene elements,without any artificial augmentation. To exemplify this situationconsider the “scene” illustrated in FIG. 13.

FIG. 13 illustrates that as in any object field 46 there will be aseries of objects of potential interest 47 scattered across the objectfield/plane. However, due to the turbulence effect termed the“isoplanatic patch size” not all of the objects in the image field willexhibit identical turbulent distortion. At any given moment, one musttherefore focus attention on a particular sub-region of the completeimage field for adaptive correction. This sub-region is typically calleda “Region of Interest” (ROI) 48. A number of commercially availablecameras allow the user to select a sub-image ROI window and to pass onlythose pixels within the window to the output image buffer at a muchhigher rate than for a full image frame.

The intent for using such a sub-image region in the image plane is tobroadly simulate the behavior of a wavefront sensor without requiringthe presence of a known light source in the object field. In any event,the placement of a single beacon or “guide star” in the object planewould not be very useful if one wished to generate corrections indifferent portions of the image plane in moderate to high turbulence.Anisoplanatism in the turbulent field would limit the angular regionover which any active beacon correction would be valid, since eachbeacon source is only useful for diagnosing turbulence errors in arelatively small angular region about its own position. Thus, for animage containing multiple ROI's, such a single known active beacon wouldbe relatively meaningless.

To apply a passive correction, several further pieces of information areneeded. The first is the time scale in which the atmosphere is expectedto vary significantly. A typical number cited is 100 Hz for ground-basedobservations. A number of factors will cause this figure to vary in ourfavor. One factor is that the wind speed is slowest closest to theground so that the turbulent field along a given path is replaced moreslowly near the surface, where ground-based sensors are designed tofunction. Another factor is that the path weighting function for theimage distortion and blur effects is largest near the system aperture,which will be typically the closest point to the ground due to terraineffects. Finally, turbulence is a function of height which is strongestclose to the ground which is the source of heating or cooling of theair. Thus the strongest turbulence that has the most effect on the imagedegradation is also the slowest evolving.

A second factor of consideration is an efficient approach toapproximating the function of a wavefront sensor. To address thisproblem reference is made to FIG. 11 (part A). If an annular aperturepattern that features a width (i.e. (D₂−D₁)/2) that is of the order ofthe coherence diameter is selected, then it is expected that phaseperturbations across the annulus will be roughly linear, but may varyaround the annulus. This suggests a pair of relationships. The phasearound the inner diameter 43 (D₁) and outer diameter 45 edges of theannular region is modeled using the following two formulas:

Φ_(inner) =A0+A1 cos(1θ)+A2 cos(2θ)+A2 cos(3θ)+A4 cos(4θ)+B1 sin(1θ)+B2sin(2θ)+B3 sin(3θ)+B4 sin(4θ)

Φ_(outer) =C0+C1 cos(1θ)+C2 cos(2θ)+C3 cos(3θ)+C4 cos(4θ)+D1 sin(1θ)+D2sin(2θ)D3 sin(3θ)+D4 sin(4θ)

Here, constants A0 through D4 are to be determined. By choosing thismodel it is possible to include up to 8 perturbation regions around theannulus, which is sufficient to correct for the first 12 Zernike terms,or effectively cover a quadrupling of the range capability.

From a practical standpoint, however, the variables Φ_(inner) andΦ_(outer) are only placeholders for the actual model of phase we wish toestimate, given by

Φ(θ,δ)=Φ_(mean)(θ)+δX _(delta)(θ),  (1)

where, instead of dealing with the inner and outer edge phases, thephase about the central ring of the annulus (44 in FIG. 11, part A) ismodeled, over which the mean phase is modeled:

Φ_(mean)=(Φ_(outer)+Φ_(inner))/2

and the radial component of the phase perturbation based on thevariable:

X _(delta)=(Φ_(outer)−Φ_(inner))/2

The reason for using a different variable type (X versus Φ) is thatX_(delta) carries a dimension of phase per delta distance. The use ofthese functions requires a coordinate system in the system annularaperture, illustrated in FIG. 14. The radii of the inner diameter D1(43) and outer diameter D2 (45) are the same as in FIG. 11, but theradial variable δ has been introduced such that δ=−1 along the innerradius and δ=+1 along the outer radius, while the azimuthal coordinate,θ, has been selected to vary in a clockwise manner.

FIG. 15 also illustrates a series of 8 radial spokes located at angles22.5, 67.5, 112.5, 157.5, 202.5, 247.5, 292.5, and 337.5 degrees fromthe origin. These radial lines denote the boundaries of 8 sampledregions subdividing the annular aperture into sub-apertures for thepurposes of constructing the estimated phase model. The approach istaken that by sampling the apparent tilt of a series of sub-apertureimages, one associated with each of these 8 regions of the annulus, itwill be possible to estimate the functional form of both Φ_(inner) andX_(delta).

To measure the tilt in each sub-aperture region of the annular aperture,a series of sub-aperture masks is applied to the aperture in succession.FIG. 16 illustrates two examples of subdivision of an annular regioninto eight sub-aperture sampling regions for two different ratios ofc=D₁/D₂.

In these figures, the dark circular region in the center (havingdiameter D₁) is the central obscuration zone of the main annularaperture. The eight overlapping circles between the inner and outercircles represent the sub-aperture circles (e.g., 50A-1, 50B-1) to betested in separate rapid image frame captures. Given that the atmosphereis evolving at a rate of 100 Hz, the eight (8) images that must becaptured to determine the current state of the phase perturbations overthe annular aperture mask must be taken at a significantly higher framerate. The Basler camera cited above can sample at rates above 3 kHz forsubframe image acquisition. At a rate of 2 kHz the Basler camera (orsuitable alternative camera) could sample the 8 sub-aperture regions in0.004 seconds, a rate fast enough to keep pace with the atmosphericevolution.

The data to be gleaned from the set of 8 sub-aperture images isschematically illustrated in FIG. 16.

To begin, prior to each image being sampled, the DMD is given aparticular sub-aperture mask 49 that will include a given sub-region 50of the total annular aperture. There are 8 sub-aperture masks (49) total(seen along the line of masks indicated by 49-1 through 49-8 in FIG.16), but where the gray regions are only to highlight the relativeposition of the windowed region (in white) as compared to the originalaperture extent bounded by the black regions.) For each sub-apertureselected, a sub-frame image is collected (as illustrated by Region ofInterest 48 in FIG. 14). As shown in FIG. 16, because each sub-apertureimage 51 is being taken through a different portion 50A, B of theoverall aperture, the apparent location of the main feature of interest52 in the sub-frame will tend to be shifted slightly from image to imagedue to differences in the wavefront tilt experienced by light arrivingfrom the object field in different portions of the system aperture. Thisshifting in position can be tracked by using matched filteringtechniques that are well known in the image processing field. The resultof this pattern matching is that a vector 53 may be assigned in eachsub-aperture image to the centroid of the main object of interest 52.This vector 53 points from a specific location on the edge of eachsub-frame 51 to the apparent centroid of the dominant image feature 52in the sub-frame 51. The set of eight vectors may be collectivelyreferred to as V_(i), where the index variable i varies from 1 to 8 (i=1. . . 8). Each V, vector is two-dimensional. Therefore, from 8sub-aperture sub-frame images 51(1-8) one obtains 8 vectors 53 thatcontain a total of 16 elements of data.

However, as was pointed out when discussing the Zernike tip and tiltterms (as shown in FIG. 4), the overall shift in location of an objectdoes not affect image quality. That is, from the standpoint of the abovesampled 8 sub-aperture images, it does not matter where the edge of thesub-frame begins, since the relative positions are all that matter. Oneway to remove such shifts in position is to compute and subsequentlyremove the effects of the origin of such vectors. This is accomplishedby computing the mean or average position of the dominant feature. Theaverage is denoted as:

V=Σ _(i) V _(i)/8

This mean shift is then subtracted from the raw vectors to produce theperturbation vectors:

V′ _(i) =V _(i) − V

Removal of the mean vector, however, means that the sum of the Vi′vectors is now zero, and two degrees of freedom have been lost since thesum of the x and y components of the vectors are now separately zero andtherefore, knowing 7 of the vectors, one can always compute the 8th.This might lead to problems because the inner and outer phase modelsintroduced just prior to Equation (1) seem to show eighteen (18)associated coefficients; whereas only 14 independent data elementsremain. However, it will be shown below that at the resolution of ourmeasurements, only 10 independent variables are required.

Consider first the mean phase function. When coefficients A0 and C0 fromthe inner and outer radius phase models are added, an average phase isobtained. The tilt created by this average will be zero. It is thereforeunmeasureable, and is in fact not needed in the correction process (itis a piston effect which does not affect image quality).

Next, observe that the model of both the sin(1θ) and cos(1θ) terms inboth the mean and delta terms is generated by a tilt that is constantover the annulus. Thus, these terms are eliminated when removing themean. Therefore, anywhere sin(1θ) and cos(1θ) terms appear in the meanor delta expansions they may be ignored. The models of the mean anddelta terms may thus be written:

Φ_(mean) =E2 cos(2θ)+E3 cos(3θ)+E4 cos(4θ)+F2 sin(2θ)+F3 sin(3θ)+F4sin(4θ)

X _(delta) =G0+G2 cos(2θ)+G3 cos(3θ)+G4 cos(4θ)+H2 sin(2θ)+H3 sin(3θ)+H4sin(4θ)

Thus, 14 data elements are sufficient to model 13 phase modelcoefficients.

To produce the equations for these 13 coefficients one must firsttranslate the measured shifts (given in pixels of shift) into phaseform. First, let IFOV denote the instantaneous field of view of a singlepixel in radians. Then, a relative shift of V_(i)′ pixels will equate toan angular shift of A_(i)′=IFOV*V_(i)′. FIG. 17 illustrates theconversion of A_(i)′ to a phase.

If, given an angular shift A′ in the radial (delta) direction, then overa distance δ′ in half-width between the center of the annulus and theedge (A_(i)′ is simply the “i”th angle of type A′), the shift that willoccur in the wavefront will be δ′*A′. But a shift of λ equates to aphase shift of 2π. That is, the physical shift translates into a phaseshift of δ′*A_(i)′*k, where k is the wavenumber, k=2π/λ. (The length δ′is used to denote the physical size of half the width of the annularring in the SLM where this phase shift must be implemented.)

In general A_(i)′ will not be directed in solely the radial direction.Therefore the radial component of A_(i)′ must be evaluated. In thefollowing discussion, these angular vectors shall be denoted A_(i)′ inorder to remind us of their vector nature. It therefore remains todetermine the radial component of each sample tilt vector. The followingsymbology is used:

A _(i)′(ρ)=ρ _(i) ·A _(i)′

to represent the “dot” (scalar) product between the angular vector andthe corresponding radial unit vector pointing from the system aperturecenter to the center of the sub-aperture (in the same angular system asin FIG. 14) for the “i”th sub-aperture image. Once the component in theradial direction is known, one may generate a phase shift for thisradial component, given by,

X _(delta)(θ_(i))=A _(i) ′kδ′

where the θ_(i)=(i−1)*π/4, i=1 . . . 8. The X_(delta) coefficients thuscan be modeled directly, and the series of values obtained can be usedto compute the expansion coefficients G0 through H4 directly. (Note thatsin(4θ)=0 at each of the θ_(i) sample locations so no contribution isobtained from evaluating H4. Therefore H4 is set to zero (H4=0)).

The process is not as straightforward for the mean phase function. Theprinciple issue is that a tilt is sampled rather than an actual phase.In this case there may be successive azimuthal mean shifts in magnitudebetween successive sub-aperture images. Nonetheless, because the meanphase could be removed, it means one can always arbitrarily shift thephase pattern produced in the azimuthal direction up or down such thatthe average is zero. The mean shift removal also removes the first ordersine and cosine dependencies. But one must still stitch togethersubsequent samples of the tilt to produce an overall function that isperiodic over 2π. A typical result is shown in FIG. 18.

To be more specific, the azimuthal component of the tilt vector for eachsample is written using the following equation:

A _(i)′(φ)=φ _(i) ·A _(i)′

Here, φ _(i) is the unit vector in the azimuthal direction for the “i”thtilt sample. Then, A_(i)′(φ) is the tilt magnitude in the azimuthaldirection for the “i”th sample. Because turbulence perturbations aretypically weak, the magnitude of these tilts will not be very large. Ascan be seen in FIG. 19, the sum of these tilts must add to zero, forotherwise the curve will not be periodic. To impose this restriction itmay be necessary to apply a correction to the set of A_(i)′(φ)'s suchthat the mean tilt can be computed as,

A _(i)′(φ)=Σ_(i) A _(i)′(φ)/8

and a corrected set of tilts can be defined as

A _(i)″(φ)=A _(i)′− A _(i)′(φ)

Such a set of azimuthal tilts ensures that any “pathological” (non-zerocurl) cases are eliminated which are mathematically possible, but whichare meaningless in terms of physically realizable phase models. Thereason for their impossibility stems from the fact that the phase is areal-valued continuous function. The tilt is a gradient operating onthis function. But the gradient of a scalar must have a zero curl.

To construct a phase model (illustrated FIGS. 19A-19F), one begins bycomputing the A_(i)″(φ) components. Then, a plot is constructed whosetotal length is π(R1+R2), which is the length around the central line(D₂ or 44 of FIG. 12A) of the annulus. Starting at the origin at theleft end of the plot, a line is traced to the point [π(R1+R2)/16,A(1)″(φ) π(R1+R2)/16], and continuing for the remaining points acrossthe graph. That is, the 8 line segments are concatenated end-to-end toform a complete azimuthal function. This graph is then equivalent to afunctional form that can be mathematically modeled and used to generatethe mean phase coefficients through mathematical integration (directly),or, more simply, through a quadrature method.

It should be noted, however, that while it is proposed to automaticallyremove the mean A_(i)′(φ), by computing this mean there is anindependent check of the fidelity of the method. Should this quantitybecome large, it is an indicator that there are phase fluctuations thatare not being accounted for in the 8 sub-aperture sampling set.

Practical Implementation Using the DMD

The Texas Instruments Digital Micromirror Device (DMD) can storeapproximately 1792 pre-loaded digital binary images in XGA format. Thissuggests that the methodology described previously in this section canbe implemented by developing several series of related image masktemplates (i.e. 1-bit images in XGA format that are downloaded to theDMD).

However, these image mask sets perform three separate tasks, only two ofwhich have been described so far. The three tasks involve differentselections of positions of the windows in the aperture depending on thefunction, and also on the underlying optical telescope for which theseoperations are performed. Consequently, different mask models are neededfor both refractor and reflector telescopes (without or with apre-existing central obscuration).

FIG. 19 illustrates several alternative apodization methods availablefor reducing the order of complexity of the random phase pattern. Thebasic models for the window masks are given in FIGS. 19A through 19F.Models 19A through 19D show the types of masks that would be used withreflector telescopes, while models 19E and 19F provide the samefunctionality for a refractor telescopic aperture that has no secondarymirror central obscuration (whose extent is denoted by circle 55 in eachapplicable figure). FIG. 19A illustrates the primary approach, where themain system aperture (60) forms the outer boundary of the annular ring.In this configuration, the inner region (55) denotes the effect of thetelescope's central secondary mirror which obscures a small centralregion of the aperture. The apodization method for this case blocks offa larger region (57) whose radius, r₁ (56), is greater than that of thesecondary mirror region (55). In FIG. 19B an inner apodization region isagain used, involving a similar approach (and numbering system denotinganalogous structures as in FIG. 19A). In addition, an outer apodizationregion is added, extending from circle 59 to system aperture 60,starting at radius r₀<D/2 (58). In FIG. 19C the same outer apodizationregion is used as in 7B, but the inner radius of the annulus is definedby the secondary mirror obscuration region (55). In FIG. 19D anon-annular region is used. This region is offset from the center of thesystem aperture by distance 61, sufficient that the circular outerobscuration region 63 of radius 62 is completely unobscured by theabsolute boundaries associated with the system entrance pupil 60 andsecondary mirror 55. In FIG. 19E a similar situation to FIG. 19D isconsidered, but involving an embodiment in which the optical system doesnot contain a secondary mirror. In this case, the radius r_(o)<D/2 (62)of the outer region can be centered on the system aperture (that is,distance 61 from 19D can be considered zero). In FIG. 19F the generalcase illustrated in FIG. 19B is again implemented, but here there is nosecondary mirror so the inner obscured region 57, of radius 56, isunrestricted in its inner diameter. The outer edge of the systemaperture is designated by the number 60. FIGS. 19D and 19E illustratereduced circular apertures necessary for the sub-aperture images. Radialvectors 56 and 58 denote the inner and outer radii of a masked annularregion. If radial vector 56 is not shown, it indicates that the maskneed not have a central obscuration in the mask itself since the systemobscuration will suffice. Similarly, if radial vector 58 is not present,it means that there is no need for a programmed outer edge of the mask.

FIG. 19D is particularly useful for purposes of building sub-aperturemasks. In this figure, 61 is an offset vector from the center of theaperture to the center of the mask's open circular region. The radius ofthe open mask region is designated as 62, the boundary of the openregion 63 through which light may pass.

Using templates similar to those shown in FIGS. 19A through 19F, sets ofmasks of different sizes and orientations may be generated and loadedonto the DMD. These masks may then be referenced by index number to actas a programmable aperture window function at any time.

FIGS. 20-25 illustrate a series of aperture mask model sets of varyingform factors and sequences. In each of these sets, the white region isthe portion of the image that will allow light to pass through the mask.The outer black and inner central obscuration regions represent opaqueportions of each mask image panel.

The mask set shown in FIG. 20 may be used to initialize the system priorto main sub-aperture testing phase. This set (some 50 to 100 masks intotal as the dots indicate intermediate forms of the mask are not shown)would be employed to sense the level of turbulence and to select areasonable initial aperture size based on the transverse coherencelength.

The mask set shown in FIG. 21 illustrates the most basic annularaperture mask set. It would be the default obscuration approach in whicha variable amount of the center of the system aperture would be blockedin producing a variable annulus width. Again, there could beapproximately 20 of these masks loaded, although the precise number mayvary as determined by those of ordinary skill in the art withoutdeparting from the scope of the invention.

The mask set shown in FIG. 22 would be an alternative to the set shownin FIG. 21. Here, instead of masking off a variable portion of thecenter of the aperture, but keeping the maximum outer radius, ifturbulence conditions are strong enough, it may be necessary to insteadmask off the outer edge of the aperture by a variable amount. Again,there could be approximately 20 of these main masks loaded on the DMD,although the precise number may vary as determined by those of ordinaryskill in the art without departing from the scope of the invention.

The mask set shown in FIG. 23 is the series of sub-aperture models thatwould be associated with the main annular mask set shown in FIG. 21. Foreach main mask of the FIG. 21 mask set, there need to be 8 sequentialmasks of the FIG. 23 type to provide sub-aperture sampling. The mask setshown in FIG. 24 serves the same function for the FIG. 22 set as the setin FIG. 23 serves for the set shown in FIG. 21.

Lastly, the set shown in FIG. 25 could be used as a further option underextreme turbulence conditions in case the central obscuration of thesystem was too large to permit characterization of the sub-aperturesaround it.

One might also consider models of 6 sub-aperture samples rather than 8,in order to increase system speed and frame rate. The resultantsub-aperture models would look similar, but would not provide the fullangular resolution of the 8 sub-aperture sample model.

The aforementioned effects of the atmosphere on a propagating wave andthe features of an optical system that could be used to detect andcorrect for atmospheric phase perturbations motivate a preferredembodiment system that may be utilized for sensing and modeling theatmospheric phase present in the system aperture. In accordance with theprinciples of the present invention, the system's spatial lightmodulator (SLM) or deformable mirror can be configured to conjugate thismeasured or modeled atmospheric phase and significantly reduce turbulentimage distortion further down the optical train. However, the method forchoosing the model of the system mask to be used must first be defined,based upon the numerous choices of mask that exist (see, for example,FIGS. 20 through 25).

Aperture Selection Procedure

For any given range, wavelength, and turbulence strength, a coherencelength may be defined:

r ₀˜3(k ² LC _(n) ²)^(−3/5)

and from the data plotted in FIG. 3 it is known that the peak of thesystem resolution curve will occur around X=D/r₀˜3. Using the series ofDMD masks shown in FIG. 20, a series of images of a scene may be taken.Let DX[i] be the equivalent aperture diameter of the “i”th mask. As longas the objects in the scene are not moving rapidly for each image in theseries one may create the sum of squares of the pixel values (afteradjusting for the mean brightness) in an ROI in the image. This sum willbe a maximum for the clearest image, which will correspond to X˜3. Foreach image, DX[i] will vary, but r₀ is expected to be approximatelyconstant; this will provide a measure of the coherence length. 20 imagesof different sizes should suffice. At a 100 frames-per-second rate, thisshould take 0.2 seconds. This operation will only need be performedoccasionally while imaging, for example, once per minute.

D_(R)=DX[imax] is set as the value of DX[i] that produced the maximumresponse of the system (i.e., i=imax). It is anticipated that D_(R) willbe slightly larger than r₀. One of the annular masks is selected where(D2−D1)/2=D_(R) from one of the annular mask sets (from FIG. 21, 22, or25), as illustrated schematically in FIG. 26.

A primary limitation in the choice of the mask that may be used derivesfrom the fact that π(D1+D2)/2 will be the circumference around the meanradius. Under the assumed constraints, the system must not require thatmore than 8 sample images be taken around that circumference. Thisimplies that, 8*2*D_(R)=8 (D2−D1) must not be less than π(D2+D1)/2, or,

(D2−D1)/(D2+D1)>π/16

Each aperture mask will thus have a restriction on the range of its D1and D2 diameters, as well as an average mask size that is related to thefull aperture size.

Overall Procedure

The steps of a preferred system procedure may comprise:

(A) Downloading a series of aperture mask patterns to the DMD Aperturecontroller (optionally selectable using an index number to the ApertureController);

Aperture Section Procedure

(B) Selecting the aperture wherein (1) the master adaptive controller(or equivalent) directs the adaptive aperture controller (or equivalent)to select one of a series of aperture masks of the type illustrated, forexample, in FIG. 21; (2) The master adaptive controller (or equivalent)directs the Adaptive Phase Controller (or equivalent) to set the SLM toneutral (no phase adjustment).

(C) Collecting of an image by the image capture module (or equivalent).

(D) Transferring the image to the image processing module (orequivalent) and producing a vector set of image quality metrics.

(E) Determining the suitability of the current FIG. 20 type mask byusing the master adaptive controller (or equivalent).

(F) Repeating steps A through E directing different choices of FIG. 20type aperture masks until it determination of an optimum aperture maskthat maximizes resolution.

(G) Storing the value of the diameter of this optimum mask as a variable(DR).

Choosing the Main Annular Mask

(H) Using the master adaptive controller (or equivalent) and the optimumtype 20 mask size (DR), the master adaptive controller (or equivalent)sets the choice of main annular mask based on a choice of one of themodel masks from FIG. 21, 22, or 25 annular mask sets.

Selecting a Region of Interest

(I) Using the master adaptive controller (or equivalent), selecting aregion of interest (ROI) in the image frame (ROI's should cycle throughthe complete image but may focus on “active” areas exhibiting changingcharacteristics from full frame to full frame).

Following Selection of an Annular Mask

Next, based on the annular mask selected . . . For (i=1 . . . 8)

(J) Using the master adaptive controller (or equivalent), directing theadaptive aperture control (or equivalent) to select one of the 8sub-aperture masks associated with the main annular mask modeldetermined in Step (H) above.

(K) Producing an image using the image capture module (or any devicecapable of producing an image).

(L) Using the master aperture control (or equivalent), directing theimage processing module (or equivalent) to load the “i”th sub-apertureframe and, through pattern matching, compare this sub-aperture frame tothe other 7 sub-aperture frames.

(M) Using the image capture module (or equivalent) capturing an imageand passing the sub-frame image to the image processing module (orequivalent).

(N) Using the image processing module (or equivalent), upon receipt ofall 8 sub-frame sub-aperture images, performing pattern matching andvector generation tasks as described in the foregoing. The perturbationvector information, V_(i)′, is passed back to the master aperturecontrol (or equivalent).

(O) Computing the phase model of the phase correction using the masteraperture control (or equivalent) in conjunction with the V_(i)′ imagemetric data passed back by the image processing module (or equivalent).(The conjugate of this information is passed to the Adaptive PhaseController which translates this information into a phase model that isthen set on the SLM).

(P) Using the master aperture control (or equivalent), directing theadaptive aperture controller to select the complete annular aperturemask.

(Q) Using the master aperture control (or equivalent), directing theimage capture module to collect a full frame image using a full framesampling dwell time of 1/200^(th) second, and making the resulting fullframe image available to an external monitor.

Steps (I) through (Q) are repeated for numerous full frame images.Recomputation of the turbulence state (following the aperture selectionprocedure of steps (B) through (H) is accomplished periodically (perhapsevery 10, 15, 20, 30, or 60 seconds), depending on the statisticalfluctuations of turbulence effects.

The preferred embodiments are effective in reduction of turbulenceeffects such as short-exposure blur, image distortion throughangle-of-arrival variations, scintillation effects, and imagedecorrelation (anisoplanatism). The importance of these effects dependson their path weighted impacts. For ground-based sensors, however,short-exposure blur effects are dominant. FIG. 27 illustrates theweighting functions of different turbulence effects: blur [75],angle-of-arrival [76], scintillation [77], and anisoplanatism [78]. Forthis daytime slant path case, the area under the blur curve issignificantly greater than that of any other effect. Also note that theweighted effect is significantly focused near the 0 end of thenon-dimensional path, where 0 is at the system receiving aperture, and 1is at the object plane. Because the blur effect is strongly dependent onturbulence close to the aperture, i.e. nearer to the ground, the windspeed causing turbulence evolution will be slower, thus reducing thetemporal tracking requirement.

The rate of evolution of turbulence features and their effects on imagephase perturbations can also be gauged relative to several features.Referring back to the FIG. 4 diagram of the Zernike polynomials, it wasnoted that in Tofsted, D. H, “Outer-scale effects on beam-wander andangle-of-arrival variances,” Appl. Opt., 31:5865-5870 (1992) (herebyincorporated by reference) the angle-of-arrival term (tip and tilt termsor n=1 row) were dominated by the length of the outer scale ofturbulence. Typical values of the outer scale are on the order of 10 m.For a typical crosswind speed between 1 and 2 m/s, this means theevolution rate for the tip-and-tilt line of the Zernike diagram is ofthe order of 1-2 Hz (for transit of a significant portion of awavelength). Analysis of the focus and astigmatism terms is shown inFIG. 28, which shows the weighted impact of turbulent spatialfrequencies of wavenumber κ normalized relative to the system diameterD. This graph reveals that the most significant wavelength affectingfocus and astigmatism is approximately 3 times the diameter.

Hence, for a system aperture of 10 cm the most significant wavelength is30 cm. At a crosswind speed of 1.5 m/s this most significant wavelengthevolves at a rate of 10-20 Hz. Hence, the evolution rate of turbulenceis higher for higher order Zernike terms, but the higher order termshave less and less effect on the overall phase. Generally, the evolutionrate of 100 Hz is considered typical for ground-based sensors. Theproposed system is designed to provide corrections within this timescale. In effect, the passive equivalent of an active-type wavefrontsensor is produced, under conditions where wavefront sensing systems areeffectively infeasible.

This system thus has the capability to perform corrections rapidly andthe capacity to control both the system aperture, thus removing certainturbulence modes, as well as providing a means of correcting the phase,which will produce a clean(er) image than could be produced by simplyreducing the aperture size.

In the preferred embodiment system, no external radiation of energy isnecessary. It thus is not a search-light or laser illuminating system,which reduces the number of systems with which it might be comparedgreatly. Likewise the system is designed to address a limited topic,namely the correction of received imagery for the effects/impacts ofoptical turbulence, and primarily the impacts of image blur that has apath weighting function that is focused just in front of the receivingaperture. Also, our system is primarily for use in ground-levelobservation. It thus does not involve mounting the device on an aircraftor moving rapidly through the atmosphere.

These considerations significantly reduce the number of practicalsystems that may have a similar claim to solving the turbulence problemfor ground based sensors. Nevertheless, the resulting problem space isnot a simple one, and involves the worst case scenario—a ground basedsensor observing distant objects through the heaviest strengthturbulence in the atmosphere. This problem is variously titled the “deepturbulence problem” or alternatively the “candlestick” problem, becauseof the shape of the 3D atmospheric envelope where systems/sensors canviably operate. In this alternative picture, a near-surface observer canview objects vertically through the atmosphere at much longer rangesthan can be done for horizontal paths.

One key to the preferred embodiment system is that no artificial guidestar is used. The system is thus truly passive; as no illuminationbeacon is propagated. For Army applications, this means that our systemis as stealthy as practical.

By not relying on a guide star, the preferred embodiment system is notbased on the detection of a coherent wavefront. The system of thepresent invention is significantly different from other systems becauseit does not require the usage of a Shack-Hartmann wavefront sensor orany other kind of wavefront sensing device. Indeed, incoherent radiationfrom any naturally illuminated or self-radiating source does not have awavefront that can be characterized by any practical wavefront sensor.This is very important, because our sensor can thus function withnatural illumination while other correction methods cannot.

Advantages

A system developed in accordance with the principles of the presentinvention provides a way for sequential compensation for turbulenceeffects in different portions of an imaged scene. Active or glint-basedsystems are only truly able to correct for the portion of a scene thatcontains the guide-star or glint itself, and may be restricted to aregion of only a few centimeters about that main region due to theimpacts of anisoplanatism in moderate optical turbulence. Conversely,the fact that turbulence close to the system aperture causes thegreatest blur means that the preferred embodiment system corrects forturbulent perturbations that have the greatest overlap for differentportions of the imaged scene.

A further innovation derives from how the proposed passive system goesabout determining the correction it applies to its SLM. Prior art hastypically relied on a method termed the SPGD (Stochastic ParallelGradient Descent) method. The SPGD method essentially attempts to“guess” the appropriate settings to place on the SLM to effect theadaptive correction. It then uses a feedback loop to decide how well itslatest guess was at correcting for the current state of the atmosphere.Consequently, an SPGD system is limited by several considerations.First, system performance is limited by frame rate. The shorter thedwell time of each frame the noisier the image will become. Second, theselected size of the system aperture is subject to two competingoptimizations. A larger aperture will allow more light to enter,reducing noise, and therefore permitting shorter dwell times per imageframe. However, turbulence near the system entrance pupil causes thelight entering the system to experience different transit time delays atdifferent points in the aperture, creating a wave that becomesincreasingly difficult to focus (increased blur). In terms of afunctional analysis of the incident wavefront, a larger system aperturerequires more Zernike expansion terms to describe the wavefront. Buteven an efficient sampling system would require roughly as many imagesamples as there are Zernike components in the incident wavefront inorder to successfully analyze it. The SPGD system, being merely aguessing/hunting technique, is far less efficient than a straightforwardanalysis such as is achieved by the Shack-Hartmann wavefront sensingtechnique. Thus to support an SPGD-based passive correction system wouldrequire an imager capable of sampling tens-of-thousands of frames persecond under high turbulence ground-to-ground imaging conditions. Whatis needed is an efficient imaging system that is capable of bothreducing the complexity of the imaging problem through a reduction inthe number of active Zernike modes, and that uses a more efficientsearch algorithm than the SPGD method.

FIG. 30 shows the general flow of information and processing stagesinvolved in control of the system. In this figure the optical system isfurther abstracted to simply show that the DMD's apodizing effects havebeen applied directly at the system entrance pupil (1). The light sourcepasses through the apodized telescope lens (21), reflects from the SLM 8and passes through the focusing lens (7) to be imaged on the imagingplane (4). The charge-coupled device (CCD) that electronically capturesthe image data at 4 communicates these data through a high speed datalink (37DATA) to a processing routine (33). The processing routine 33assesses the quality of the current image using selected controlsettings designated for the DMD (21) and SLM (8) via controller commandlinks 103S and 105S, respectively. These command signals are driven bycontrol software modules for the DMD (103) and SLM (105). The controllersoftware sub-modules 103 and 105 tailor a specific choice of settingsfor these devices based on a control directing master module (106) thatreceives current status information concerning the most recent settingsof the SLM and DMD from the image quality evaluation module 33 via datalink 38DATA. The settings for the next image frame to be collected aresent to the two controller modules via data links 106SA and 106SB.

FIG. 31 illustrates a key concept explaining how the combination of aDigital Micro-mirror Device with a Spatial Light Modulator overcomes ageneral limitation of most passive adaptive systems. That limitation isthat the feedback used by the system (data signals 37DATA and 38DATA inFIG. 30) only supplies a general metric (the sum square of pixel valuesin a region of interest). However, the resulting feedback does notindicate a specific direction of improvement of the signal. Hence,presumably, one would need to sample all 12 modes to yield a singlecorrection direction. However, as FIG. 7B illustrates, the presence of acentral obscuration should reduce the complexity of the coherent patchpattern. FIG. 31 offers a comparison of four pairs of radial Zernikemodels that feature the same azimuthal dependence (same f parameter),but differ in their radial dependencies. FIG. 31 Graph A compares Z₂ ⁰(90) with Z₄ ⁰ (91), FIG. 31 Graph B compares Z₁ ¹ (92) with Z₃ ¹ (93),FIG. 31 Graph C compares Z₂ ² (94) with Z₄ ² (95), FIG. 31 Graph Dcompares Z₃ ³ (96) with Z₄ ² (97). The point of these comparisons isthat although they appear to show differences in their central regions,in the region beyond approximately |p|>0.8 each function isapproximately linear. Since it is known that each pair has the same findex, then they share the same azimuthal dependence. The effect of thecentral obscuration is thus to effectively map Zernike terms onto oneanother vertically, as long as the central obscuration is a large enoughfraction of the full aperture

The system of the present invention is optimized to require a minimumnumber of image samples to be collected in order to track the evolvingstate of the turbulent atmosphere. The result is reduced overall noise.

A further innovation is based on an exploitation of a feature of theaperture apodization technique. Because an annular aperture is formedusing the DMD, (1) the number of active Zernike modes in the remainingaperture is reduced, thereby reducing the number of sample images thatmust be collected in order to make a current atmospheric state analysis,and (2) the means of analyzing the phase perturbations present in theaperture is simplified, producing a method that can track theatmospheric perturbations even more efficiently than a simple circularaperture. The reason the number of active Zernike modes is reduced isbecause the annular-shaped apodization pattern effectively causes anumber of Zernike modes to map onto one another. It therefore makes theprocess of assessing the state of the turbulent blur perturbationseasier.

Moreover, an annular aperture also allows the system to have a largereffective aperture for a given pupil area. That is, for a given numberof active Zernike modes, because the annular aperture causes certainmodes to overlap one another, for a given total area (assuming the samenumber of modes per unit area) an aperture with a hole in the centerwill feature an overall wider outer radius. But the maximum angularfrequency response of the system depends on the maximum diameter passed.Therefore, an annular aperture of equal area as a circular aperture willalways feature a higher maximum frequency response, and therefore agreater image resolution, all other things being equal. And with greaterangular frequency resolution, overall, an annular system's rangecapability is automatically greater than that of a circular aperturesystem of equal area.

Another innovation is the placement of the system apodization controldevice (the DMD) inside the system optical train. This appears to beunique; i.e. using a DMD to provide automatic aperture apodizationcontrol. Also, because a DMD is used, the speed of the aperture responseis virtually instantaneous. This permits the system to perform a seriesof aperture adjustments for studying the properties of turbulencearriving at various portions of the system aperture in a manneranalogous to the wavefront sensing techniques used in active systems,but where the DMD is substituted for the operations of theShack-Hartmann sensor.

The apodization control both limits the degree of complexity of theatmospheric correction problem, to facilitate the correction sensingprocess, and optimizes both the solution speed and frequency responsefunction of the system. To achieve this apodization control, the DMD isused as a surrogate for the actual system aperture is if the DMD isplaced at a real image plane of the system aperture. The mechanismwhereby this real image plane can be formed is by using at least twopositive lenses. The first of these lenses must be placed close to theexit pupil of the system's telescope prior to its natural focal point,so that the focal point is shortened, creating a more rapidly divergingwave subsequent to the focal point. This beam is then passed through asecond positive lens that produces a parallel beam similar to thewavefront upon entry through the system's entrance pupil prior toreaching the first (primary) mirror. The DMD is then placed at a focalpoint of the system aperture so that when the DMD aperture is modifiedit cuts off an equivalent amount of light from the original waveentering the system.

FIG. 32 illustrates the impact of the central obscuration on thecomplexity of the tracking task that must be accomplished by theproposed invention. As has already been discussed, the first threeZernike terms in box 68 of FIG. 32 (piston, tip, and tilt) should notaffect image quality. The subsequent 12 terms on the next three rowscovering the Focus and Astigmatism row, the Coma and Clover row, and the4th order row constitute the 12 terms described by Hufnagel whosecorrection satisfy the 12 DoC line of FIG. 5. However, based on theprior discussion of FIG. 31, with the addition of the apertureapodization, the three shaded elements of the 4th order line (including70) will be effectively mapped upon (69) by elements of the Focus andAstigmatism row. A similar effect will occur when elements of the Comaand Clover row map onto elements of a 5^(th) row which was not includedin this Figure. It is also an open question whether or not the Comaelements (Z₃ ⁻¹ and Z₃ ¹) of the third row will be mapped upon by thetip and tilt elements (Z₁ ⁻¹ and Z₁ ¹) such that these do not need to beactively tracked either. If this were the case, it would be possible totrack the 12 elements using only 7 terms. Otherwise it would require 9terms.

Attention is now turned to the question of the feasibility of the methoditself to track either 7 or 9 Zernike terms, providing correctionssufficient to remove these terms from the incident phase front. Toaddress this issue, this is first discussed in general terms the natureof the problem being addressed and the expected rate of evolution of thevarious terms.

FIG. 33 is the first of two figures illustrating the application areaconsidered relevant to our invention. This figure focuses on the pathweighting functions applicable to four separate image distortion effects(hence the title given to the vertical axis of the plot). The verticalaxis denotes the weight factor that multiplies the turbulence strengthvalue (Co₂) at each position along the optical path. The four effectsare long exposure blur (71), parameterized by the coherence diameter ro,amplitude scintillations (72), parameterized by the scintillationlog-variance, the isoplanatic angle (73) that characterizes the dividingof the viewed object plane into independently moving (due toangle-of-arrival) patches, and the angle-of-arrival variance whichcharacterizes how large the image distortions from one point will be inangle from its actual position (74). These functions are plottedrelative to a normalized horizontal axis path position where u=Ocorresponds to the receiver system aperture and u=1 is the object plane.The critical aspect of this plot is to illustrate that the image blureffect is weighted most heavily toward the system aperture while theremaining effects are weighted toward either the center of the path,uniformly along the path, or toward the object plane end of the opticalpath.

FIG. 34 illustrates that differences in path weighting factors, whencombined with the height dependence of daytime turbulence produces acritical synergy between the turbulence strength and the path weightingfactor to highlight the significant degradations of imaging capabilitydue to image blur for surface-based imaging systems. During daylighthours, a common rule is to consider turbulence strength to diminish as afunction of the height above the surface to the minus 4/3rds power. InFIG. 34 the height of the receiver is simulated as 2 m above groundlevel (AGL), a viewed object is placed at 34 m AGL at a range of 2 kmdistant. Thus the viewed object appears to be 1 degree of arc above thehorizon. For this scenario, and using normalized weighting functions,the image mean blur (75) greatly outweighs the effect ofangle-of-arrival (76), scintillation (77), or isoplanatic angle (78).This order of effects reveals the significance of blur for surface-basedimaging sensors. One should note, however, that the coherence diameterthat characterizes the blur effect is scaled according K^(−6/5) whichimplies that blur effects diminish at longer wavelengths.Angle-of-arrival effects are practically wavelength independent, meaningthat at long-wave infrared wavelengths angle-of-arrival is the dominantterm, even for surface based sensors.

FIG. 28 illustrates one of the remaining questions with regard to theviability of the proposed method. Although FIGS. 33 and 34, combined,suggest that if one could remove the blur effects from imagery, it wouldbe possible to perceive objects at increased range with more clarity,the question remains how fast the atmosphere may be evolving and whetheror not a system could have sufficient bandwidth to track suchvariations. To explore this, reference is first made to the paperentitled Tofsted, D. H, “Outer-scale effects on beam-wander andangle-of-arrival variances,” Appl. Opt., 31:5865-5870 (1992) (herebyincorporated by reference) exploring outer scale of turbulenceinfluences on image angle of arrival. There, it was reported that theturbulence spectral frequency most responsible for angle-of-arrival wasof the order of size of the turbulence outer scale. For regions close tothe surface (termed the surface layer, a region within 50-100 m of theground) the outer scale of turbulence is a few meters in length. Thus,for the first two Zernike perturbation terms (the tip and tilt terms),the dominant turbulent length scale affecting these terms is the outerscale, or a length scale larger than the system aperture diameter (whichis considered for the application environment to be fixed to less than30 em, i.e. D<0.30 m). For the next row of Zernike polynomials downwardin the FIG. 32 table (the Focus and Astigmatism line), one may determinethe most effective size of turbulence by considering a single spatialfrequency of turbulence centered about the system aperture and ask whatsize of turbulence will create the greatest phase perturbation. On theone hand, for a turbulence perturbation wave of spatial wavelength A andwavenumber K=2rr/λ the phase change between the center of the opticalaperture and the edge of the aperture will be ΔΦl>=2π[1−cos(KD/2]. Onthe other hand, due to the decreasing magnitude of the turbulence powerspectrum which decreases in the inertial subrange at the rate,K^(−11/3), and thus will decrease in amplitude at a rate of K^(−11/6),one may plot the function [1−cos(X)] X^(−11/6) in FIG. 28 to reveal thatthe peak of this function occurs at X=0.9914. That is, the maximumeffective perturbation wavelength is approximately A=πD. Thus, the mosteffective wavelength is larger than the system aperture. For example,for a nominal aperture of D=10 cm, the most effective wavelength wouldbe approximately 30 cm. One must also consider that in the near surfaceatmosphere refractive turbulence is strongest when convective mixing ofthe air is dominant over mechanical mixing due to high wind speeds. Highwinds tend to more efficiently remove heat from the ground, and morerapidly mix variable temperature air, reducing the turbulence strength.Thus for the present application environment, the conditions under whichturbulence is most effective occurs when wind speeds are the lowest,thus leading to a condition where the rate of evolution of theatmosphere is relatively low.

Considering the previous scenario, assuming a wind speed at 2 m equal 2rn/s. This is a nominal speed often seen on hot desert days whenturbulence strength is highest. Under this condition, the most effectivewavelength for impacting focus and astigmatism would evolve at (2.0rn/s)/0.3 m or 6.7 Hz. For a 1 m outer scale, the tip and tiltvariations would occur at a rate of approximately 2 Hz. Hence,successive rows of Zernike polynomials appear to exhibit increasingrates of evolution. Conversely, higher order terms appear to have adiminishing effect on image clarity. Thus the job of trackingperturbations should be within the realm of the achievable, given animaging system that can operate at a frame rate 10-20 times faster thanthe rate of evolution, sufficient to produce several guesses of thecorrect current settings of the Zernike coefficients within theevolution timeframe of each evolving term to be tracked.

FIG. 35 illustrates a key factor in the feasibility of any method ofimage correction based on adaptive techniques. FIG. 35 shows an abstractexample of this problem. A typical scenario involves a system withaperture (79) far smaller than the imaged field (81). Typical sizes ofthe aperture (10 cm), imaged object (50 cm), and range to object (80) of2 km are indicated. For this scenario one may consider a visible bandsystem operating at a mean wavelength in the green portion of thespectrum of λ.=0.55 μm, and a strong turbulence regime of C_(n) ²=10⁻¹³m^(−2/3) at 2 m height. For this scenario, if the terrain were flat suchthat the object viewed is at the same height as the sensor, thecoherence diameter would equal: r_(o)=3.018(k²LC_(n) ²)^(−3/5)=6.8 mm,resulting in a ratio X=D/r₀=14.8. Alternatively, for the slant pathscenario indicated in FIG. 28, using the turbulence strength indicatedhere, r₀=17.6 mm resulting in a reduced X=5.7. For this scenario acoherence length may also be computed that is weighted toward the objectend of the path, resulting in r₀=48.0 mm. This parameter is diagnosticof characteristic sizes on the object that will appear to experienceindependent angle-of-arrival fluctuations (i.e. are in separateisoplanatic regions), as characterized by the isoplanatic angle which isapproximately r₀/L.

Note that the effects of anisoplanatism (objects extending to dimensionslarger than an isoplanatic region) affect every adaptive system,creating independently wandering patches of the imaged object in theimage plane. Therefore any imaging system may need to be augmented by aseparate image post-processing system that stitches clear sub-imagestogether (i.e., a lucky patch technique) and dewarping of the image.However, such a system is inadequate to remove the impacts ofshort-exposure blur, which is the principle objective of the currentinvention. Based on the scenario outlined above, one expects that forthe indicated turbulence level, the value of the parameter X will besomewhere between 5 and 15, indicating that the performance of any luckyimage based system will be severely degraded by the atmospheric scenariopresented.

Equally true, for active adaptive systems involving laser illuminationof an object plane one of two situations will occur: Either theillumination pulse will be focused within a single isoplanatic region onthe object plane, or it will not. The first case may also be consideredto include the case of an active illuminator placed directly at theobject plane to serve as a guide star type source. If the first instanceoccurs, then the active imager's wavefront-detection-based solution willbe strictly applicable only for the particular isoplanatic patch fromwhich the guide beacon emerges. If the second instance obtains, then theactive imager's solution will be derived from multiple independentisoplanatic regions exhibiting independent statistics, making itdifficult to imagine how the solution from these independently emittingregions can produce anything resembling a coherent wave at the receiversystem's aperture suitable for analysis by a Shack-Hartmann wavefrontsensor. Hence, although a passive sensor system might initially appearinferior to an active adaptive system, for extended scene objects whichare larger than the isoplanatic patch size, a non-illuminating passiveapproach appears at least as reasonable and entailing less risk than anyactive system approach.

Also included in FIG. 35 are lines (82) extending from the outer edgesof the entrance pupil to outer edges of the viewed object. Theseextended lines illustrate that there is a region of the path in whichlines from opposing sides of the aperture pass through approximatelyidentical optical turbulence, particularly turbulence of the size scalesthat most affect the lowest order modes of the Zernike perturbationexpansion functions. This region is approximately of length (83), andrepresents a greater or lesser portion of the path depending on theextent of separation of the points considered in the object plane.However, notice that for the scenario considered above, a regionconsisting of a single isoplanatic patch of dimension −5 cm is a sizethat is less than the diameter of the aperture and thus corresponds inthe figure a region of extent (84), connected to the aperture via dashedlines (85). For such a section of the image, the correspondingatmospheric elements accounting for virtually all of the blurringeffects over this section are identical for this section of the objectplane. A passive system could thus be directed by a control softwareprogram to direct its blur corrections to addressing a single portion ofthe image, and systematically work to improve image quality over amosaic of the object plane, in any sort of static imaging scenario. Fordynamically varying portions of any object scene, it would be possibleto track these dynamic elements by focusing the system's correctionattentions on a particular portion or even a dynamically changingportion.

FIG. 36 is an additional preferred embodiment of the present invention.FIG. 36 is identical to FIG. 7A, thus retaining the same numberingsystem and definitions as described in that figure, but replacing theadaptive SLM with a mirror 99 in the optical system. Such an embodimentis not a complete version of the invention, but represents a possibleintermediate stage of development as well as a more economical systemfor some applications as the cost of the SLM is significantly largerthan that of the DMD 21. By limiting the adaptive method to onlymodifying the aperture shape according to the selection optionsindicated in FIGS. 19A through 19F, and, in particular, apodizationmethods of FIGS. 19D and 19E, it may be possible to restrict the numberof independent coherence regions present in the effective receiveraperture, thereby improving image quality, albeit at the expense ofoverall diffraction limited capability. For such a system the form ofthe control architecture would be equally truncated, removing elementsSLM 8, 105, and 105S from FIG. 30.

It is noted that the assemblies described herein could work inassociation with either a reflector telescope or a refractor telescope.In addition, the reflector (system with reflector mirror objective) orrefractor telescope (system with refractor lens or off-axis mirrorwithout central obstruction) combination could be connected to either aDMD-only embodiment or a DMD+SLM embodiment; thereby creating fourpossible embodiments. That would seem to make 4 possible embodiments,etc. In addition, a preferred embodiment could operate with a deformablemirror instead of the SLM (in addition to the DMD). A preferredembodiment combination may operate using (a) control software operatingusing a single sum of squares metric for the full image or (b) controlsoftware operating using a sum of squares metric multiplied by aGaussian window focusing on a portion of the image frame. A preferredembodiment combination (DMD-only embodiment or a DMD+SLM) embodiment mayoptionally include a system in which the user may select a region ofinterest for weighted improvement scheme. Optionally, a preferredembodiment combination (DMD-only embodiment or a DMD+SLM) may optionallyinclude mosaicing software to merge image portions. Optionally, apreferred embodiment combination (DMD-only embodiment or a DMD+SLM) mayoptionally include monitoring software to assess portions of an imageframe which appear to have significantly changed triggering focusedrelook and update. Optionally, a preferred embodiment combination(DMD-only embodiment or a DMD+SLM) may optionally include image dewarpprocedure applied to deblurred image.

As used herein, the terminology “target” means a person or persons, orportion thereof, animal or animals, thing, object, or a combinationthereof

As used herein the terminology “point of interest” or “points ofinterest” refer to an signature or area in the image which appears to bea target but may or may not be a target; i.e., potentially the point ofinterest may be a target; subject to further processing or testing.

As used herein, the terminology adjustable apodizer includes but is notlimited to the Digital-Micro-mirror Device (DMD). One key to theadaptive aperture controller or DMD 21 is that the center of the systemaperture is variably obscured.

As used herein the terminology “processor” includes computer,controller, CPU, microprocessor, multiprocessor, minicomputer, mainframe, personal computer, PC, coprocessor, and combinations thereof orany machine similar to a computer or processor which is capable ofprocessing algorithms.

As used herein the terminology apodization means changing the shape of amathematical function, an electrical signal, or an optical transmission.

As used herein the terminology the terminology “process” means: analgorithm, software, subroutine, computer program, or methodology.

As used herein the terminology “target signature” means thecharacteristic pattern of a target displayed by detection andidentification equipment.

As used herein, the terminology “algorithm” means: sequence of stepsusing computer software, process, software, subroutine, computerprogram, or methodology.

As used herein, the terminology “optical train” or “optical assembly”means the arrangement of lenses and/or elements to guide light throughthe system to form an image at the image plane. The position and angleof lenses or elements may be adjustable to guide light along the opticalpath.

As used herein, the terminology “plane of incidence” is the planespanned by the surface normal to the optical axis. In wave optics, thelatter is the k-vector of the incoming wave.

As used herein, the terminology “image plane” means the plane in whichan image produced by an optical system is formed; if the object plane isperpendicular to the optical axis, the image plane will ordinarily alsobe perpendicular to the axis. As used herein, the terminology “principalplane” means a plane that is perpendicular to the axis of a lens,mirror, or other optical system and at which rays diverging from a focalpoint are deviated parallel to the axis or at which rays parallel to theaxis are deviated to converge to a focal point.

The foregoing description of the specific embodiments are intended toreveal the general nature of the embodiments herein that others can, byapplying current knowledge, readily modify and/or adapt for variousapplications such specific embodiments without departing from thegeneric concept, and, therefore, such adaptations and modificationsshould and are intended to be comprehended within the meaning and rangeof equivalents of the disclosed embodiments. It is to be understood thatthe phraseology or terminology employed herein is for the purpose ofdescription and not of limitation. Therefore, while the embodimentsherein have been described in terms of preferred embodiments, thoseskilled in the art will recognize that the embodiments herein can bepracticed with modification within the spirit and scope of the appendedclaims.

1. A method for reducing the effects of turbulence comprising: providingan opening for entrance of light; the light being capable of beingformed into an image; providing a plurality of optical elements in anoptical train configured to focus light; providing a variable apertureoperatively associated with the at least one optical element; thevariable aperture being placed in the optical train at an image planeand comprising mask settings for shielding portions of the light;providing an imager; providing at least one processor operativelyconnected to the variable aperture and imager; the at least oneprocessor configured to control the passage of the light through thevariable aperture; selectively masking portions of light using the masksettings of the variable aperture; obtaining image results using thesettings; comparing image results obtained by the mask settings, anddetermining the mask settings that provides the optimal image results.2. The method of claim 1 wherein blur effects related to atmosphericperturbations affecting image quality are mitigated and wherein themethod further comprises: providing a spatial light modulator positionedin the optical train and operating to modulate the phase of a light beamspatially; the spatial light modulator being placed in a Fourier planeof the system; forming a coordinated pair of correction signals appliedto a variable aperture of an optical correction system and a spatiallight modulator, the variable aperture allowing variable amounts oflight to pass therethrough and assessing feedback from an imager oflight passing though the variable aperture and spatial light modulatorusing the at least one processor; the at least one processor assigningcurrent settings to the variable aperture and spatial light modulatorbased upon results of current and/or previous settings of the variableaperture and spatial light modulator.
 3. The method of claim 2 whereinthe step of selectively masking portions of light using mask settingscomprises using first mask settings for shielding portions of the lightand second mask settings for selectively sampling portions of the lightthat would have passed through the first mask settings.
 4. The method ofclaim 3 wherein the step of determining the mask results comprisesdetermining a first mask setting that provides an optimal image resultwherein the first masks are annular masks.
 5. The method of claim 1wherein the image of a scene of interest cannot be seen clearly by anunaided telescopic imager due to the presence of turbulence, and whereinthe variable aperture comprises a programmable digital mirror devicecontrolled by micro-electro-mechanical pivoting members which allowvariable amounts of light to pass therethrough according topredetermined programmable mask settings.
 6. The method of claim 3wherein the second mask settings comprise a sequence of circular secondmask settings of different diameters that are sequentially implementedand wherein the images are collected and analyzed for image clarity todetermine the optimal selection of the next first mask setting forturbulence currently present.
 7. The method of claim 3 wherein theopening for entrance light enables the entrance of a plurality of lightwave fronts arising from an object scene; the plurality of light wavefronts being capable of forming an image at the image plane; theplurality of light wave fronts passing through the plurality of opticalelements that focuses the light wave fronts onto the image plane; thefirst mask settings of the variable aperture operating to shieldportions of the light wave fronts and the second mask settings operatingto selectively mask portions of the light wave fronts that wouldotherwise pass through the first mask setting; and wherein the imager isconfigured to collect the wavefronts; and wherein the method furthercomprises providing a wavefront corrector and a controller algorithmoperatively associated with the at least one processor; the at least oneprocessor configured to control the passage of light through thevariable aperture by: selecting one of plurality of first mask settingsand its associated second mask settings; obtaining a sequence ofintermediate sample image results using the settings; comparing imageresults obtained by the respective mask settings, determining an optimalwavefront corrector correction for reducing the effects of turbulencecurrently present, applying the correction setting to the wavefrontcorrector; and collecting a full frame image using settingscorresponding to the optimal first mask setting and wavefront correctionsetting determined.
 8. The method of claim 7 wherein the wavefrontcorrector comprises a plurality of settings, the plurality of settingscomprising piston adjustments that adjust a sequence of deformablemirror pistons by performing fluctuations of the current choice ofpiston settings.
 9. The method of claim 7 wherein the first masksettings are annular and the wavefront corrector is controlled by the atleast one processor based upon the results obtained using previoussettings of the variable aperture and wavefront corrector.
 10. Themethod of claim 8 wherein the first mask setting is annular and thewavefront corrector piston adjustment settings are set by the at leastone processor based upon the results obtained from analysis of multipletest images collected under previous settings of the variable apertureand wavefront corrector and a plurality of test images at the range ofapproximately 1/5000^(th) to 1/500th second are collected and used toobtain information about the turbulent effects of the atmosphere, andsubsequently a longer exposure image in the range of 1/1000th to 1/50 ofa second is obtained using updated settings of the wavefront correctorand the previous setting of the variable aperture.
 11. The method ofclaim 7 wherein the wavefront corrector comprises a spatial lightmodulator operatively associated with the at least one processor, andwherein light is passed through the variable aperture using a sequenceof second mask settings to collect and analyze a sequence ofsub-aperture images, and wherein the at least one processor operates tocompare the results obtained by the image capture device for thesequence of sub-aperture images using pattern matching to detect angleof arrival offsets between different images collected through differentportions of the first mask setting to provide a wavefront tiltcorrection solution for the spatial light modulator.
 12. The method ofclaim 7 wherein the plurality of optical elements comprises at least onelens operatively associated with the variable aperture such that thelight passes through at least one lens before entering the variableaperture and wherein the first plurality of mask settings comprise aplurality of annular masks settings, each annular mask settingselectively masking portions of the light, allowing light to pass in theshape of an annulus that permits the maximum angular frequency responseof the system.
 13. The method of claim 3 wherein the imager has a methodfor producing a sub-aperture image containing at least one region ofinterest having a designated point, and whereby by drawing a vector froma predetermined point on the periphery of the sub-aperture image to thedesignated point a vector having a magnitude and direction is producedfor each sub-aperture image of the associated first mask setting, thevector magnitude and direction being utilized by the at least oneprocessor as feedback for control of the variable aperture and spatiallight modulator to improve image quality, and wherein the at least oneprocessor is configured to use the second mask settings associated withthe first mask settings to create sub-aperture frames comprising adifferent area within the annulus of light passed by the associatedfirst annular mask setting, and wherein at least one processor isconfigured to select a region of interest in the sub-aperture frames,compare each sub-aperture frame to the other sub-aperture frames usingpattern matching and perform vector generation based upon a vectorgenerated from the periphery of the sub-aperture frame to a point in theregion of interest.
 14. The method of claim 1 wherein the variableaperture is controlled by a first controlling algorithm on the at leastone processor and wherein the method further comprises providing aspatial light modulator controlled by a second controlling algorithm onthe at least one processor and a feedback control circuit to test theclarity of the images or pattern matching offsets between sub-apertureimages being produced by the current settings of the optical adjustmentsof the variable aperture and spatial light modulator.
 15. A method ofmitigating blur effects related to atmospheric perturbations affectingimage quality in an imaging system comprising: forming a coordinatedpair of correction signals applied to a variable aperture of an opticalcorrection system and a spatial light modulator, the variable aperturebeing positioned in the optical train in a real image plane of theentrance pupil and allowing variable amounts of light to passtherethrough and the spatial light modulator being positioned in theoptical train and operating to modulate the phase of a light beamspatially; the spatial light modulator being placed in a Fourier planeof the system; assessing feedback from an imager of light passingthrough the variable aperture and spatial light modulator using at leastone processor; the at least one processor assigning current settings tothe variable aperture and spatial light modulator based upon results ofcurrent and/or previous settings of the variable aperture and spatiallight modulator.
 16. The method of claim 15 further comprising:providing an opening for entrance of light; the light being capable ofbeing formed into an image; providing a plurality of optical elements inan optical train configured to focus light; the variable aperture beingoperatively associated with the at least one optical element; thevariable comprising mask settings for shielding portions of the light;providing an imager; the at least one processor operatively connected tothe variable aperture and imager; the at least one processor configuredto control the passage of the light through the variable aperture;selectively masking portions of light using the mask settings of thevariable aperture; obtaining image results using the settings; comparingimage results obtained by the mask settings, and determining the masksettings that provide the optimal image results.
 17. The method of claim15 wherein the variable aperture comprises a digital micro-mirror deviceand wherein the variable aperture comprises a main central obscurationzone of the main annular aperture, and wherein overlapping circularareas between the inner and outer circles of the main annular apertureproduce sub-aperture frames to be tested in separate image framecaptures, and wherein each sub-aperture frame produced comprises aregion of interest selected by at least one processor, and wherein theat least one processor sequentially cycles through the regions ofinterest to sequentially produce improved images of different portionsof the complete system field of view wherein each sub-aperture frame setgenerates vectors based upon pattern matching, and wherein the vectorinformation is processed by the at least one processor to generatecorrection signals to the variable aperture and spatial light modulatorto improve image quality for each region of interest, and wherein thevectors based upon pattern matching by the at least one processor areused to compute the phase model of the phase correction, which is passedto an adaptive phase controller which translates this information into aphase model that is then set on the spatial light modulator, and whereinthe at least one processor operates to direct a variable aperturecontroller to control selection of an annular aperture mask.
 18. Amethod of reducing the effects of turbulence in an imaging devicecomprising: (a) selecting one of a series of aperture masks; (b) settingphase modulation adjustment of a spatial light modulator to neutral (c)capturing an image using an imager; (d) creating a vector set of imagequality metrics from the captured image; (e) determining the suitabilityof the mask selected; (f) repeating steps (a) though (e) until anoptimum aperture mask is selected based upon maximizing resolution; (g)storing the value of the annular ring width of the optimum annularaperture mask as a variable DR, where (D2−D1)/2=DR and D2 is the outerdiameter and D1 is the inner diameter of an annular aperture mask; (h)using the optimum annular ring width DR, and based on the availablechoices of masks satisfying this width criterion, selecting the mainannular mask based on a choice of one of a group of annular mask setssatisfying this criteria; (i) selecting a region of interest in theimage frame containing a feature of interest; the region of interestbeing obtained by cycling through the complete image while focusing onactive areas exhibiting changing characteristics from full frame to fullframe; (j) selecting a plurality of sub-aperture masks associated withthe main annular mask determined in step (h); each of the plurality ofsub-aperture masks defining a sub-aperture image containing the sameregion of interest; (k) for each sub-aperture image, performing patternmatching of the selected sub-aperture image by computing the relativeshift in position of the selected sub-aperture image region of interestin each sub-aperture image, and generating a vector defining thelocation of the main feature of interest in each of the sub-apertureimages, each vector originating from a predetermined location on theedge of each sub-aperture image frame and pointing to the centroid ofthe dominant image feature in each sub-aperture frame; and (l) computinga wavefront correction.
 19. The method of claim 18 wherein the averagephase adjustment is computed by first considering the mean phase usingthe coefficients A0 and C0 from the inner and outer radius phase modelsto obtain an average phase around the inner diameter and outer diameterof the annular region using the following two formulas:Φ_(inner) =A0+A1 cos(1θ)+A2 cos(2θ)+A2 cos(3θ)+A4 cos(4θ)+B1 sin(1θ)+B2sin(2θ)+B3 sin(3θ)+B4 sin(4θ)Φ_(outer) =C0+C1 cos(1θ)+C2 cos(2θ)+C3 cos(3θ)+C4 cos(4θ)+D1 sin(1θ)+D2sin(2θ)D3 sin(3θ)+D4 sin(4θ) where θ is the azimuthal coordinate, andwherein the tilt created by the average phase adjustment average will bezero, and wherein both the sin(1θ) and cos(1θ) terms in both the meanand delta terms is generated by a tilt that is constant over the annulusand the sin(1θ) and cos(1θ) terms are eliminated when removing the mean,and wherein the constants A0 through D4 are determined by completing thesteps of claim 19, and where the variables Φ_(inner) and Φ_(outer) areonly placeholders for the actual model of phase that is estimated givenby,Φ(θ,δ)=Φ_(mean)(θ)+δX _(delta)(θ) and wherein instead of using the innerand outer edge phases, the phase about the central ring of the annulusis modeled, over which the mean phase is modeled:Φ_(mean)=(Φ_(outer)+Φ_(inner))/2 and the radial component of the phaseperturbation is based on the variable:X _(delta)=(Φ_(outer)−Φ_(inner))/2 and wherein the use of thesefunctions requires a coordinate system in the system annular aperture,such that the radial variable δ has been introduced such that δ=−1 alongthe inner radius and δ=+1 along the outer radius, θ, is the azimuthalcoordinate, and wherein the models of the mean and delta terms may bewritten as:Φ_(mean) =E2 cos(2θ)+E3 cos(3θ)+E4 cos(4θ)+F2 sin(2θ)+F3 sin(3θ)+F4sin(4θ)X _(delta) =G0+G2 cos(2θ)+G3 cos(3θ)+G4 cos(4θ)+H2 sin(2θ)+H3 sin(3θ)+H4sin(4θ) whereby to use the 13 phase model coefficients E2, E3, E4, F2,F3, F4, G0, G2, G3, G4, H2, H3, and H4, the measured phase shift ofpixels are first translated into phase form wherein IFOV denotes theinstantaneous field of view of a single pixel in radians, and a relativeshift of Vi′ pixels will equate to an angular shift of Ai′=IFOV*Vi′, andif given an angular shift in the radial (delta) direction, then over aspace δ in half-width between the center of the annulus and the edge,for an angle Ai′, the shift that must take place in the wavefront willbe δ*Ai′ which translates into a phase shift of δ*Ai′*k, where k is thewavenumber, k=2α/λ and the radial component of each sample tilt vectoris computed using Ai′(ρ)=ρi·Ai′ to represent the scalar product betweenthe angular vector and the corresponding radial unit vector pointingfrom the system aperture center to the center of the sub-aperture forthe “i”th sub-aperture image; and$\overset{\_}{V} = {\sum\limits_{i = 1}^{i = I}\; {V_{i}/I}}$ where Vrepresents the mean vector, V_(i) represents the vector for eachsub-aperture image and I is the number of sub-aperture images, andwherein the mean vector is subtracted from vectors V_(i) to produce theperturbation vectors V_(i)′:V′ _(i) =V _(i) − V and wherein that the sum of the perturbation V_(i)′vectors is equal to zero, and wherein the perturbation vectorinformation, V_(i)′, is used by the at least one processor to computethe phase model of the phase correction and the conjugate of thisinformation is passed to an adaptive phase controller which translatesthis information into a phase model that is then set on the spatiallight modulator and the at least one processor operates to direct anadaptive aperture controller to cause the variable aperture to selectthe complete annular aperture mask.